[ WebToolTip.com ] Udemy - Production-Grade Deep Learning Pipelines

Creation Time	Oct. 25, 2026, 10:53 p.m.
Last Access Time	Oct. 25, 2026, 10:58 p.m.
File Size	3.1 GB
Keywords	Pipelines WebToolTip - Deep Udemy Learning Production-Grade com
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Total Files	411
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~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/90. Lab - Building, Training, and Tracking the DNN with MLflow.mp4 111.0 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/167. Lab - Running the Local Pipeline.mp4 88.5 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/297. Lab - Pipeline-Run Function - Adding a New Span.mp4 80.4 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/132. Lab - The Tuner Module File.mp4 79.2 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/141. Lab - The Trainer Module File.mp4 78.8 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/269. Lab - Model-Push Cloud Function.mp4 75.6 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/294. Lab - Pipeline-Run (Retraining) Cloud Function.mp4 72.0 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/228. Lab - Pipeline Run Script - Compile and Submit.mp4 68.6 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/221. Lab - Pipeline Initialization and Run.mp4 62.4 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/50. Lab - Data Ingestion and Span Splitting.mp4 52.5 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/268. Walkthrough - The Model-Push Cloud Function - Auto-Deploy on a New Model.mp4 52.0 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/159. Lab - Building the Base Pipeline.mp4 50.1 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/293. Walkthrough - The Pipeline-Run Cloud Function - Retraining on a New Span.mp4 48.9 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/217. Walkthrough - Schema Handling Across Local and Cloud Pipelines.mp4 48.8 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/145. Lab - Evaluator.mp4 45.6 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/124. Lab - Transform.mp4 44.9 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/148. Lab - Pusher Results.mp4 44.2 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/168. Lab - Local Beam Runner.mp4 39.3 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/101. Lab - TFX Imports and Libraries.mp4 37.5 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/232. Lab - Docker Image and Pipeline Files on GCP.mp4 36.1 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/220. Lab - Helper Functions.mp4 33.2 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/308. Walkthrough - CI-CD with GitHub Actions - submit-vertex.yml.mp4 32.8 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/144. Lab - Resolver - Latest Blessed Model.mp4 32.6 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/265. Lab - Deploying to a Vertex AI Endpoint.mp4 31.4 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/62. Lab - Feature Engineering and Standardization.mp4 31.3 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/216. Walkthrough - Pipeline Composition - Training and Evaluation Windows.mp4 30.1 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/214. Lab - Cloud Pipeline Introduction.mp4 28.1 MB
~Get Your Files Here !/33 - Lesson 8.2 – Vertex AI Model Registry - Versioning Before Serving/258. Lab - Vertex AI Model Registry.mp4 27.8 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/166. Lab - Setting Up Logging.mp4 27.1 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/106. Lab - ExampleGen.mp4 26.4 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/267. Lab - Serving Online Predictions.mp4 26.2 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/300. Lab - Pipeline-Run Function - New Model (Part 2).mp4 26.2 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/299. Lab - Pipeline-Run Function - New Model (Part 1).mp4 26.0 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/314. Lab - GitHub Secrets.mp4 26.0 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/113. Lab - SchemaGen.mp4 25.1 MB
~Get Your Files Here !/30 - Lesson 7.4 – The Vertex AI Pipelines UI and Artifact Lineage/241. Lab - Inspecting the Vertex AI Pipeline Run.mp4 24.9 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/89. Lab - Loading and Preprocessing the Data.mp4 23.9 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/158. Lab - Local Pipeline Introduction.mp4 23.2 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/313. Lab - Workload Identity Pool.mp4 23.1 MB
~Get Your Files Here !/30 - Lesson 7.4 – The Vertex AI Pipelines UI and Artifact Lineage/240. Lab - Running the Pipeline on Vertex AI.mp4 21.9 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/121. Lab - Anomalies and Validation Outcomes.mp4 21.7 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/310. Lab - GitHub Account and Repository Setup.mp4 19.8 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/312. Lab - Service Account Permissions.mp4 19.7 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/131. Lab - Tuner Component.mp4 19.4 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/109. Lab - StatisticsGen.mp4 18.3 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/201. Lab - Creating the GCS Bucket.mp4 18.3 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/219. Lab - Imports and Constants.mp4 17.8 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/114. Lab - Inspecting the Schema File.mp4 16.0 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/321. Known Failure Modes of Automated ML Systems.mp4 15.9 MB
~Get Your Files Here !/31 - Lesson 7.5 – Scheduling, Triggering, and Production Operations/243. Scheduled Triggering.mp4 14.4 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/298. Lab - New Span Added - Pipeline Triggered.mp4 14.2 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/289. Alert Configuration.mp4 14.1 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/320. The Boundaries of Automation.mp4 14.1 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/229. Lab - Dockerfile for the Pipeline Image.mp4 13.2 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/317. Lab - CI-CD Running on GitHub and GCP.mp4 12.4 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/188. Lab - GCP Console Introduction.mp4 12.1 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/305. What the Monitoring System Cannot Do Automatically.mp4 12.0 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/218. Lab - Cloud Base Pipeline Overview.mp4 11.6 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/147. Lab - Pusher.mp4 10.9 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/215. Walkthrough - Spans Explained - How Spans Drive the Cloud Pipeline.mp4 9.2 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/318. Lab - Inspecting Cloud Storage After the Run.mp4 9.1 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/328. Pipeline Parameterization.mp4 8.8 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/303. Lab - When the New Model Is Not Blessed.mp4 8.6 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/102. Lab - Pipeline Data Directory.mp4 8.6 MB
~Get Your Files Here !/41 - Lesson 10.2 – Cost Optimization and Production Efficiency/334. Storage Cost Optimization.mp4 8.3 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/134. Lab - Best Hyperparameters.mp4 8.1 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/311. Lab - Creating the GCP IAM Service Account.mp4 8.0 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/139. Lab - Trainer Component.mp4 7.9 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/226. The Execution Lifecycle of a Pipeline Run.mp4 7.8 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/162. What Changes from InteractiveContext to LocalDagRunner.mp4 7.7 MB
~Get Your Files Here !/43 - Lesson 10.4 – Course Retrospective and What Comes Next/343. What This Course Didn't Cover.mp4 7.7 MB
~Get Your Files Here !/41 - Lesson 10.2 – Cost Optimization and Production Efficiency/333. Compute Cost Optimization.mp4 7.5 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/307. The Complete Feedback Loop.mp4 7.4 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/36. Lab - Dataset Overview.mp4 7.4 MB
~Get Your Files Here !/43 - Lesson 10.4 – Course Retrospective and What Comes Next/342. The Skills You Now Have.mp4 7.2 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/302. The Resolver and Baseline Comparison.mp4 7.1 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/316. Lab - Changing a File and Testing Locally.mp4 7.1 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/65. Lesson 3.1 - DNN Architecture - Design and Build.mp4 7.1 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/296. What the Retraining Pipeline Does Differently.mp4 7.0 MB
~Get Your Files Here !/42 - Lesson 10.3 – MLOps Team Practices and Documentation/340. Change Management for ML Systems.mp4 6.8 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/329. Multi-Span Training Strategies.mp4 6.7 MB
~Get Your Files Here !/36 - Lesson 9.1 – Why Models Degrade - Drift, Skew, and Silent Failures/278. Lesson 9.1 - Why Models Degrade - Drift, Skew, and Silent Failures.mp4 6.7 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/323. What a Production ML System Actually Looks Like.mp4 6.5 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/326. The Boundaries of Standard TFX Components.mp4 6.4 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/327. Custom TFX Components - When and Why.mp4 6.3 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/262. Endpoint Configuration.mp4 6.3 MB
~Get Your Files Here !/31 - Lesson 7.5 – Scheduling, Triggering, and Production Operations/245. Module 7 as the Completion of MLOps Level 1.mp4 6.3 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/211. The Architecture Shift.mp4 6.3 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/103. Lesson 4.2 - Data Ingestion - ExampleGen, StatisticsGen, SchemaGen.mp4 6.1 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/128. Bayesian Optimization - Smart Search.mp4 6.0 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/304. Lab - New Model Versions in the Registry.mp4 6.0 MB
~Get Your Files Here !/41 - Lesson 10.2 – Cost Optimization and Production Efficiency/335. Pipeline Efficiency - Caching and Smart Reruns.mp4 6.0 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/95. Three Foundational TFX Concepts.mp4 5.9 MB
~Get Your Files Here !/36 - Lesson 9.1 – Why Models Degrade - Drift, Skew, and Silent Failures/281. Training-Serving Skew.mp4 5.9 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/71. Architecture Concepts.mp4 5.9 MB
~Get Your Files Here !/41 - Lesson 10.2 – Cost Optimization and Production Efficiency/332. The True Cost of a Production ML System.mp4 5.8 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/91. Module Overview - Introducing TFX.mp4 5.8 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/291. The Event-Driven Trigger Chain.mp4 5.8 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/247. Lesson 8.1 - From Artifact to Service - The Deployment Model.mp4 5.8 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/319. What Level Two Means Operationally.mp4 5.8 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/330. The Challenger Model Pattern.mp4 5.8 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/26. The Unified Data-Flow Diagram.mp4 5.7 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/68. The create_dnn_model Function.mp4 5.7 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/274. Traffic Splitting - Canary Deployments and Safe Rollouts.mp4 5.7 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/119. Lab - ExampleValidator.mp4 5.7 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/208. Lesson 7.1 - From LocalDagRunner to Vertex AI Pipelines.mp4 5.5 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/288. Statistical Detection Methods.mp4 5.5 MB
~Get Your Files Here !/29 - Lesson 7.3 – Distributed Execution - Vertex AI Training/235. Vertex AI Training.mp4 5.5 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/231. Lab - requirements.txt.mp4 5.5 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/287. Skew Detection vs Drift Detection.mp4 5.5 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/28. Lesson 1.5 - Case Study Deep Dive.mp4 5.4 MB
~Get Your Files Here !/12 - Lesson 3.3 – MLflow Experiment Tracking/78. Lesson 3.3 - MLflow Experiment Tracking.mp4 5.4 MB
~Get Your Files Here !/36 - Lesson 9.1 – Why Models Degrade - Drift, Skew, and Silent Failures/279. Data Drift.mp4 5.4 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/212. Component Isolation.mp4 5.3 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/322. The Full Course Arc - Module 1 to Module 9.mp4 5.3 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/55. Lesson 2.3 - Feature Engineering Concepts and Standardization.mp4 5.3 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/195. Lesson 6.3 - Google Cloud Storage as the New Artifact Store.mp4 5.3 MB
~Get Your Files Here !/11 - Lesson 3.2 – Compiling, Callbacks, and Training/73. Compilation.mp4 5.3 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/200. Data Governance in GCS.mp4 5.3 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/224. The Pipeline Spec.mp4 5.2 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/207. Module Overview - Cloud Pipeline Orchestration.mp4 5.2 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/272. Batch Prediction.mp4 5.2 MB
~Get Your Files Here !/36 - Lesson 9.1 – Why Models Degrade - Drift, Skew, and Silent Failures/280. Concept Drift.mp4 5.2 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/67. The Three Layer Building Blocks.mp4 5.2 MB
~Get Your Files Here !/26 - Lesson 6.4 – Preflight - What Must be True Before Module 7/206. The Irreversibility Principle.mp4 5.1 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/120. Lab - ExampleValidator Results.mp4 5.1 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/286. The Training Baseline.mp4 5.1 MB
~Get Your Files Here !/29 - Lesson 7.3 – Distributed Execution - Vertex AI Training/234. Distributed Execution in the Pipeline.mp4 5.1 MB
~Get Your Files Here !/12 - Lesson 3.3 – MLflow Experiment Tracking/80. MLflow Core Concepts.mp4 5.0 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/197. Buckets, Objects, and URIs.mp4 5.0 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/301. Lab - Pipeline-Run Function - Pipeline JSON.mp4 5.0 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/196. What GCS Is.mp4 5.0 MB
~Get Your Files Here !/31 - Lesson 7.5 – Scheduling, Triggering, and Production Operations/244. Pipeline Versioning.mp4 4.9 MB
~Get Your Files Here !/8 - Lesson 2.2 – Exploratory Data Analysis/54. From EDA to Schema - The Production Connection.mp4 4.9 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/84. Evaluating on the Test Set.mp4 4.8 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/225. Submission.mp4 4.8 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/250. The Three-Step Deployment Path.mp4 4.7 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/306. Lesson 9.4 - The Complete Feedback Loop - Level 2 Achieved.mp4 4.7 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/173. Gap 3 - No Pipeline Monitoring UI.mp4 4.7 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/252. Why the Registry and Endpoint are Separate.mp4 4.7 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/249. Model as File vs Model as a Service.mp4 4.6 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/96. The Interactive Context.mp4 4.6 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/251. The Serving Signatures in Production.mp4 4.6 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/64. Module Overview - Local Model Development & Experimentation.mp4 4.6 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/259. Lesson 8.3 - Vertex AI Endpoints - Managed TF Serving at Scale.mp4 4.6 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/186. The GCP Project.mp4 4.6 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/266. Request Flow.mp4 4.6 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/25. Layer 5 - Serving and CI-CD (TF Serving, Docker, GitHub Actions).mp4 4.6 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/223. Why Compilation Is Needed.mp4 4.5 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/86. Learning Curves.mp4 4.5 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/261. TF Serving Under the Hood.mp4 4.5 MB
~Get Your Files Here !/29 - Lesson 7.3 – Distributed Execution - Vertex AI Training/236. Why Distributed Execution Changes the Scale Equation.mp4 4.5 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/160. Lesson 5.2 - Running Locally - LocalDagRunner and Artifact Caching.mp4 4.5 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/142. The Evaluator.mp4 4.5 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/260. What a Vertex AI Endpoint Is.mp4 4.5 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/93. The Problem Modules 2 and 3 Left Unsolved.mp4 4.4 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/30. The 8 Input Features.mp4 4.4 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/295. Span 2 as the Drift Simulation.mp4 4.4 MB
~Get Your Files Here !/24 - Lesson 6.2 – Identity and Access Management/191. User Accounts vs Service Accounts.mp4 4.4 MB
~Get Your Files Here !/36 - Lesson 9.1 – Why Models Degrade - Drift, Skew, and Silent Failures/277. Module Overview - Monitoring & Automated Retraining.mp4 4.4 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/70. Note on Kernel Regularizer.mp4 4.4 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/154. What is a DAG.mp4 4.3 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/246. Module Overview - Deployment in the Cloud.mp4 4.3 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/263. Autoscaling.mp4 4.3 MB
~Get Your Files Here !/26 - Lesson 6.4 – Preflight - What Must be True Before Module 7/205. Cost Awareness.mp4 4.3 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/88. model.save() and the SavedModel Format.mp4 4.3 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/23. Layer 3 - Pipeline Orchestration (TFX + Apache Beam).mp4 4.3 MB
~Get Your Files Here !/33 - Lesson 8.2 – Vertex AI Model Registry - Versioning Before Serving/257. The Registry as the Source of Truth for Production State.mp4 4.2 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/199. GCS as Connective Tissue.mp4 4.2 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/56. The Feature Engineering Landscape.mp4 4.1 MB
~Get Your Files Here !/24 - Lesson 6.2 – Identity and Access Management/193. The Principle of Least Privilege.mp4 4.1 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/163. Artifact Caching.mp4 4.1 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/164. Cache Hit vs Cache Miss.mp4 4.1 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/66. Sequential vs. Functional API.mp4 4.1 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/117. Severity Levels.mp4 4.0 MB
~Get Your Files Here !/33 - Lesson 8.2 – Vertex AI Model Registry - Versioning Before Serving/255. What a Model Version Record Contains.mp4 4.0 MB
~Get Your Files Here !/8 - Lesson 2.2 – Exploratory Data Analysis/51. Lesson 2.2 - Exploratory Data Analysis.mp4 4.0 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/230. Lab - Request JSON.mp4 3.9 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/275. Endpoint Monitoring.mp4 3.9 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/183. The Mental Model Shift.mp4 3.9 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/24. Layer 4 - Cloud Infrastructure (GCP + Vertex AI).mp4 3.9 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/111. The Conditional Schema Pattern.mp4 3.9 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/284. What Vertex AI Model Monitoring Is.mp4 3.9 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/155. How TFX Derives the DAG Automatically.mp4 3.9 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/271. Real-Time Prediction.mp4 3.9 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/57. Why We Keep FE Minimal in This Course.mp4 3.8 MB
~Get Your Files Here !/30 - Lesson 7.4 – The Vertex AI Pipelines UI and Artifact Lineage/239. The DAG View.mp4 3.8 MB
~Get Your Files Here !/1 - Lesson 1.1 - Welcome and Course Roadmap/1. Module Overview - Introduction & Local Setup.mp4 3.8 MB
~Get Your Files Here !/24 - Lesson 6.2 – Identity and Access Management/190. The IAM Model.mp4 3.8 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/33. Why Deep Learning.mp4 3.8 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/123. The Transform Graph Artifact.mp4 3.8 MB
~Get Your Files Here !/26 - Lesson 6.4 – Preflight - What Must be True Before Module 7/204. Infrastructure vs Code Readiness.mp4 3.8 MB
~Get Your Files Here !/33 - Lesson 8.2 – Vertex AI Model Registry - Versioning Before Serving/256. Connection to TFX Pusher and MLMD Lineage.mp4 3.8 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/136. Trainer.mp4 3.8 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/126. Why HP Tuning Belongs in the Pipeline.mp4 3.8 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/175. Portability Promise.mp4 3.7 MB
~Get Your Files Here !/42 - Lesson 10.3 – MLOps Team Practices and Documentation/338. Model Cards.mp4 3.7 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/171. Gap 1 - No Scheduling or Automated Triggering.mp4 3.7 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/21. Layer 1 - Modeling (TensorFlow-Keras).mp4 3.7 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/105. Why TFRecord.mp4 3.7 MB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/264. The Deployed Model Resource.mp4 3.7 MB
~Get Your Files Here !/2 - Lesson 1.2 – What is the ML Lifecycle/11. Phase 3 - Monitoring.mp4 3.7 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/181. Module Overview - Transition to the Cloud.mp4 3.7 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/143. The Resolver.mp4 3.7 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/151. Module Overview - Orchestrating Local Pipelines.mp4 3.6 MB
~Get Your Files Here !/12 - Lesson 3.3 – MLflow Experiment Tracking/82. The train_dnn_model Function Logs.mp4 3.6 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/324. Module Overview - Advanced Topics & Wrap-Up.mp4 3.6 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/227. Run IDs, Run History, and the Metadata Store.mp4 3.6 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/276. Module 8 in the Course Arc.mp4 3.6 MB
~Get Your Files Here !/32 - Lesson 8.1 – From Artifact to Service - The Deployment Model/248. The Deployment Gap.mp4 3.6 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/43. Module Overview - Local Data & Feature Engineering.mp4 3.6 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/187. What Enabling an API Means.mp4 3.6 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/185. GCP Services Map.mp4 3.6 MB
~Get Your Files Here !/36 - Lesson 9.1 – Why Models Degrade - Drift, Skew, and Silent Failures/282. Why Silent Degradation Is the Hardest Failure Mode.mp4 3.6 MB
~Get Your Files Here !/24 - Lesson 6.2 – Identity and Access Management/194. IAM as the Enabler of Production Automation.mp4 3.6 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/156. The Pipeline Object.mp4 3.6 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/149. The Complete Pipeline.mp4 3.6 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/153. The Gap Between Module 4 and Production.mp4 3.6 MB
~Get Your Files Here !/33 - Lesson 8.2 – Vertex AI Model Registry - Versioning Before Serving/254. What the Model Registry Is.mp4 3.6 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/45. What is a Data Span.mp4 3.6 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/22. Layer 2 - Experiment Management (MLflow).mp4 3.5 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/172. Gap 2 - No Failure Recovery.mp4 3.5 MB
~Get Your Files Here !/22 - Lesson 5.4 – The Road to Cloud/179. What Changes at Each Level.mp4 3.5 MB
~Get Your Files Here !/2 - Lesson 1.2 – What is the ML Lifecycle/10. Phase 2 - Deployment.mp4 3.5 MB
~Get Your Files Here !/33 - Lesson 8.2 – Vertex AI Model Registry - Versioning Before Serving/253. Lesson 8.2 - Vertex AI Model Registry - Versioning Before Serving.mp4 3.5 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/170. What LocalDagRunner Does Well.mp4 3.4 MB
~Get Your Files Here !/26 - Lesson 6.4 – Preflight - What Must be True Before Module 7/203. The Preflight Checklist.mp4 3.4 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/285. How Vertex AI Model Monitoring Obtains Data.mp4 3.4 MB
~Get Your Files Here !/29 - Lesson 7.3 – Distributed Execution - Vertex AI Training/233. Lesson 7.3 - Distributed Execution - Vertex AI Training.mp4 3.4 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/97. Apache Beam - The Execution Engine.mp4 3.4 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/129. The Search Space in build_dnn_model.mp4 3.4 MB
~Get Your Files Here !/3 - Lesson 1.3 – ML Maturity Stages/13. Lesson 1.3 - ML Maturity Stages.mp4 3.4 MB
~Get Your Files Here !/2 - Lesson 1.2 – What is the ML Lifecycle/9. Phase 1 - Development.mp4 3.4 MB
~Get Your Files Here !/41 - Lesson 10.2 – Cost Optimization and Production Efficiency/336. Cost Attribution.mp4 3.4 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/165. MLMD as Execution History Across Runs.mp4 3.4 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/210. What Vertex AI Pipelines Is.mp4 3.3 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/63. TFX Transform - What Changes in Module 4.mp4 3.3 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/94. What TFX Is.mp4 3.3 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/118. Why This Gate Matters in Production.mp4 3.3 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/112. What a Schema Encodes.mp4 3.3 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/122. Transform.mp4 3.3 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/83. Lesson 3.4 - Evaluation, Visualization, and Model Serving.mp4 3.3 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/116. ExampleValidator.mp4 3.2 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/152. Lesson 5.1 - The Pipeline Object - Assembling the DAG.mp4 3.2 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/138. Dual Serving Signatures.mp4 3.2 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/34. Evaluation Metrics.mp4 3.2 MB
~Get Your Files Here !/3 - Lesson 1.3 – ML Maturity Stages/17. Level 2 - CI-CD Pipeline Automation.mp4 3.2 MB
~Get Your Files Here !/24 - Lesson 6.2 – Identity and Access Management/192. Roles the ML Pipeline Service Account Needs.mp4 3.2 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/182. Lesson 6.1 - GCP as the Production ML Infrastructure.mp4 3.2 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/135. Lesson 4.5 - Training, Evaluation, and Deployment.mp4 3.2 MB
~Get Your Files Here !/16 - Lesson 4.3 – Data Validation and Transformation/115. Lesson 4.3 - Data Validation and Transformation.mp4 3.2 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/35. Real-World Production Context.mp4 3.1 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/127. Keras Tuner - The Tuning Framework.mp4 3.1 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/104. ExampleGen.mp4 3.1 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/46. How Production Spans Are Generated.mp4 3.1 MB
~Get Your Files Here !/25 - Lesson 6.3 – Google Cloud Storage as the New Artifact Store/198. Mapping the Pipeline Directory Structure to GCS.mp4 3.1 MB
~Get Your Files Here !/22 - Lesson 5.4 – The Road to Cloud/180. The Complete Course Arc.mp4 3.1 MB
~Get Your Files Here !/11 - Lesson 3.2 – Compiling, Callbacks, and Training/74. Early Stopping.mp4 3.1 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/92. Lesson 4.1 - TFX - From Scripts to Pipelines.mp4 3.1 MB
~Get Your Files Here !/12 - Lesson 3.3 – MLflow Experiment Tracking/79. The Problem MLflow Solves.mp4 3.1 MB
~Get Your Files Here !/11 - Lesson 3.2 – Compiling, Callbacks, and Training/75. Reduce Learning Rate on Plateau.mp4 3.1 MB
~Get Your Files Here !/42 - Lesson 10.3 – MLOps Team Practices and Documentation/339. Data Cards.mp4 3.1 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/137. Steps vs Epochs.mp4 3.0 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/48. Train-Test-Eval Roles.mp4 3.0 MB
~Get Your Files Here !/8 - Lesson 2.2 – Exploratory Data Analysis/53. Dataset Profile - What to Look For.mp4 3.0 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/213. The Portability Confirmation.mp4 3.0 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/110. SchemaGen.mp4 3.0 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/60. The Fit-Transform Function.mp4 3.0 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/100. Lab - TFX Notebook Introduction.mp4 3.0 MB
~Get Your Files Here !/24 - Lesson 6.2 – Identity and Access Management/189. Lesson 6.2 - Identity and Access Management.mp4 3.0 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/29. Dataset Origin and Provenance.mp4 2.9 MB
~Get Your Files Here !/23 - Lesson 6.1 – GCP as the Production ML Infrastructure/184. Why GCP.mp4 2.9 MB
~Get Your Files Here !/22 - Lesson 5.4 – The Road to Cloud/178. The Three-Level View of the Pipeline.mp4 2.9 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/32. Problem Framing - Why Regression.mp4 2.9 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/108. StatisticsGen.mp4 2.9 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/174. Gap 4 - No Team Access or Governance.mp4 2.9 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/176. When Local Orchestration is the Right Choice.mp4 2.9 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/273. Choosing Between Real-Time and Batch.mp4 2.8 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/58. Standard Scaler.mp4 2.8 MB
~Get Your Files Here !/3 - Lesson 1.3 – ML Maturity Stages/16. Level 1 - ML Pipeline Automation Experiments.mp4 2.8 MB
~Get Your Files Here !/20 - Lesson 5.2 – Running Locally - LocalDagRunner and Artifact Caching/161. LocalDagRunner - The Local Orchestrator.mp4 2.8 MB
~Get Your Files Here !/10 - Lesson 3.1 – DNN Architecture - Design and Build/69. Output Layer Design for Regression.mp4 2.8 MB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/157. The Pipeline as a Versionable Artifact.mp4 2.8 MB
~Get Your Files Here !/40 - Lesson 10.1 – Advanced Pipeline Patterns/325. Lesson 10.1 - Advanced Pipeline Patterns.mp4 2.8 MB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/31. The Target Variable.mp4 2.7 MB
~Get Your Files Here !/1 - Lesson 1.1 - Welcome and Course Roadmap/5. Course Structure.mp4 2.7 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/44. Lesson 2.1 - Data Ingestion & The Spans Concept.mp4 2.7 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/61. The Scaler as a Pipeline Artifact.mp4 2.7 MB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/59. The Data Leakage Rule.mp4 2.7 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/309. Lab - Local Development Folder for CI-CD.mp4 2.7 MB
~Get Your Files Here !/1 - Lesson 1.1 - Welcome and Course Roadmap/3. What Problem Does This Course Solve.mp4 2.7 MB
~Get Your Files Here !/2 - Lesson 1.2 – What is the ML Lifecycle/12. Where Projects Fail.mp4 2.7 MB
~Get Your Files Here !/11 - Lesson 3.2 – Compiling, Callbacks, and Training/77. Dataset Shuffle.mp4 2.7 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/20. Why See the Full Stack First.mp4 2.7 MB
~Get Your Files Here !/26 - Lesson 6.4 – Preflight - What Must be True Before Module 7/202. Lesson 6.4 - Preflight - What Must be True Before Module 7.mp4 2.6 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/146. The Pusher.mp4 2.6 MB
~Get Your Files Here !/1 - Lesson 1.1 - Welcome and Course Roadmap/4. What You Will Build.mp4 2.6 MB
~Get Your Files Here !/30 - Lesson 7.4 – The Vertex AI Pipelines UI and Artifact Lineage/238. The Pipeline Run List.mp4 2.6 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/130. The tuner_fn Interface.mp4 2.6 MB
~Get Your Files Here !/21 - Lesson 5.3 – The Limits of Local Orchestration/169. Lesson 5.3 - The Limits of Local Orchestration.mp4 2.6 MB
~Get Your Files Here !/28 - Lesson 7.2 – Pipeline Compilation and the Execution Model/222. Lesson 7.2 - Pipeline Compilation and the Execution Model.mp4 2.6 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/99. TFX and the MLOps Maturity Model.mp4 2.5 MB
~Get Your Files Here !/41 - Lesson 10.2 – Cost Optimization and Production Efficiency/331. Lesson 10.2 - Cost Optimization and Production Efficiency.mp4 2.5 MB
~Get Your Files Here !/8 - Lesson 2.2 – Exploratory Data Analysis/52. EDA as a Production Discipline.mp4 2.5 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/140. Lab - Trainer Results.mp4 2.5 MB
~Get Your Files Here !/3 - Lesson 1.3 – ML Maturity Stages/15. Level 0 - Manual ML.mp4 2.5 MB
~Get Your Files Here !/15 - Lesson 4.2 – Data Ingestion - ExampleGen, StatisticsGen, SchemaGen/107. Lab - Pipeline Root.mp4 2.4 MB
~Get Your Files Here !/11 - Lesson 3.2 – Compiling, Callbacks, and Training/72. Lesson 3.2 - Compiling, Callbacks, and Training.mp4 2.4 MB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/37. Lesson 1.6 - Setting Up Your Local Development Environment.mp4 2.3 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/87. The plot_metric Function.mp4 2.3 MB
~Get Your Files Here !/2 - Lesson 1.2 – What is the ML Lifecycle/7. Lesson 1.2 - What is the ML Lifecycle.mp4 2.3 MB
~Get Your Files Here !/2 - Lesson 1.2 – What is the ML Lifecycle/8. The Three Phases.mp4 2.3 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/19. Lesson 1.4 - The Complete Production ML Tool-Stack.mp4 2.3 MB
~Get Your Files Here !/30 - Lesson 7.4 – The Vertex AI Pipelines UI and Artifact Lineage/237. Lesson 7.4 - The Vertex AI Pipelines UI and Artifact Lineage.mp4 2.2 MB
~Get Your Files Here !/3 - Lesson 1.3 – ML Maturity Stages/14. Why Maturity Frameworks Matter.mp4 2.2 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/125. Lesson 4.4 - Hyperparameter Tuning with Keras Tuner.mp4 2.2 MB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/270. Lesson 8.4 - Real-Time vs Batch, Traffic Management, and Production Operations.mp4 2.2 MB
~Get Your Files Here !/12 - Lesson 3.3 – MLflow Experiment Tracking/81. Running the MLflow Server.mp4 2.2 MB
~Get Your Files Here !/11 - Lesson 3.2 – Compiling, Callbacks, and Training/76. The train_dnn_model Function.mp4 2.1 MB
~Get Your Files Here !/3 - Lesson 1.3 – ML Maturity Stages/18. Where This Course Takes You.mp4 2.1 MB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/85. R Squared.mp4 2.1 MB
~Get Your Files Here !/31 - Lesson 7.5 – Scheduling, Triggering, and Production Operations/242. Lesson 7.5 - Scheduling, Triggering, and Production Operations.mp4 2.1 MB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/209. Recap.mp4 2.1 MB
~Get Your Files Here !/1 - Lesson 1.1 - Welcome and Course Roadmap/6. Prerequisites.mp4 2.0 MB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/39. Environment Discipline Is a Production Practice.mp4 1.9 MB
~Get Your Files Here !/17 - Lesson 4.4 – Hyperparameter Tuning with Keras Tuner/133. The Best Hyperparameters Artifact.mp4 1.9 MB
~Get Your Files Here !/4 - Lesson 1.4 – The Complete Production ML Tool-Stack/27. Tool Passport.mp4 1.9 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/49. Directory Structure.mp4 1.9 MB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/315. Lab - The submit-vertex.yml Workflow.mp4 1.8 MB
~Get Your Files Here !/1 - Lesson 1.1 - Welcome and Course Roadmap/2. Lesson 1.1 - Welcome and Course Roadmap.mp4 1.7 MB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/47. Span Structure.mp4 1.6 MB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/150. Lab - Inference with the Pushed Model.mp4 1.6 MB
~Get Your Files Here !/37 - Lesson 9.2 – Vertex AI Model Monitoring - Configuration and Detection/283. Lesson 9.2 - Vertex AI Model Monitoring - Configuration and Detection.mp4 1.4 MB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/41. Python Version.mp4 1.3 MB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/98. Pipeline Directory Structure.mp4 1.2 MB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/290. Lesson 9.3 - From Alert to Action - Automated Retraining with Span 2.mp4 1.1 MB
~Get Your Files Here !/22 - Lesson 5.4 – The Road to Cloud/177. Lesson 5.4 - The Road to Cloud.mp4 1.1 MB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/42. Core Packages.mp4 849.7 KB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/40. Git - Version Control from Day One.mp4 758.9 KB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/4_tfx_pipeline.ipynb 540.7 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/01_experimentation/4_tfx_pipeline.ipynb 540.7 KB
~Get Your Files Here !/43 - Lesson 10.4 – Course Retrospective and What Comes Next/341. Lesson 10.4 - Course Retrospective and What Comes Next.mp4 297.6 KB
~Get Your Files Here !/42 - Lesson 10.3 – MLOps Team Practices and Documentation/337. Lesson 10.3 - MLOps Team Practices and Documentation.mp4 287.9 KB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/2_feature_eng.ipynb 220.3 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/01_experimentation/2_feature_eng.ipynb 220.3 KB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/62. 2_feature_eng.ipynb.bin 220.3 KB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/38. Before You Begin - Setting Up Linux with WSL.pdf 179.3 KB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/89. 3_model_arch.ipynb.bin 132.5 KB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/3_model_arch.ipynb 132.5 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/01_experimentation/3_model_arch.ipynb 132.5 KB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/292. Lab Note - How Retraining Is Triggered in Module 9.pdf 67.9 KB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/9. Quiz 9.html 27.0 KB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/1. Quiz 1.html 25.9 KB
~Get Your Files Here !/18 - Lesson 4.5 – Training, Evaluation, and Deployment/4. Quiz 4.html 25.8 KB
~Get Your Files Here !/9 - Lesson 2.3 – Feature Engineering Concepts and Standardization/2. Quiz 2.html 25.6 KB
~Get Your Files Here !/13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/3. Quiz 3.html 25.6 KB
~Get Your Files Here !/35 - Lesson 8.4 – Real-Time vs Batch, Traffic Management, and Production Operations/8. Quiz 8.html 25.5 KB
~Get Your Files Here !/31 - Lesson 7.5 – Scheduling, Triggering, and Production Operations/7. Quiz 7.html 25.5 KB
~Get Your Files Here !/26 - Lesson 6.4 – Preflight - What Must be True Before Module 7/6. Quiz 6.html 25.4 KB
~Get Your Files Here !/22 - Lesson 5.4 – The Road to Cloud/5. Quiz 5.html 25.2 KB
~Get Your Files Here !/43 - Lesson 10.4 – Course Retrospective and What Comes Next/10. Quiz 10.html 25.1 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/pipeline.json 24.5 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/pipeline.json 24.5 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/README.md 15.5 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/base_pipeline.py 15.2 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/base_pipeline.py 15.2 KB
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~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/module.py 13.2 KB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/02_local_pipeline/module.py 13.2 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/module.py 13.2 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/01_experimentation/module.py 13.2 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/02_local_pipeline/module.py 13.2 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/module.py 13.2 KB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/02_local_pipeline/base_pipeline.py 10.2 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/02_local_pipeline/base_pipeline.py 10.2 KB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/292. Lab Note How Retraining Is Triggered in This Module.html 8.6 KB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/02_local_pipeline/pipeline_run.py 7.2 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/02_local_pipeline/pipeline_run.py 7.2 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/pipeline_run.py 6.4 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/pipeline_run.py 6.4 KB
~Get Your Files Here !/34 - Lesson 8.3 – Vertex AI Endpoints - Managed TF Serving at Scale/269. gcp_cloud_run_func_model-push.py 6.1 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/04_cloud_run_functions/gcp_cloud_run_func_model-push.py 6.1 KB
~Get Your Files Here !/38 - Lesson 9.3 – From Alert to Action - Automated Retraining with Span 2/294. gcp_cloud_run_func_pp-run.py 5.8 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/04_cloud_run_functions/gcp_cloud_run_func_pp-run.py 5.8 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/requirements.txt 5.3 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/requirements.txt 5.3 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/requirements.txt 5.3 KB
~Get Your Files Here !/6 - Lesson 1.6 – Setting Up Your Local Development Environment/38. requirements.txt 5.3 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/docs/setup-wsl.md 5.3 KB
~Get Your Files Here !/14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/1_data_ingest.ipynb 4.8 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/01_experimentation/1_data_ingest.ipynb 4.8 KB
~Get Your Files Here !/7 - Lesson 2.1 – Data Ingestion & The Spans Concept/50. 1_data_ingest.ipynb.bin 4.8 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/36. prepare_data.py 4.6 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/prepare_data.py 4.6 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/docs/module-9-lab-note.md 2.2 KB
~Get Your Files Here !/19 - Lesson 5.1 – The Pipeline Object - Assembling the DAG/02_local_pipeline/setup_logging.py 2.1 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/02_local_pipeline/setup_logging.py 2.1 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/setup_logging.py 2.1 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/setup_logging.py 2.1 KB
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/github/workflows/submit-vertex.yml 2.1 KB
~Get Your Files Here !/39 - Lesson 9.4 – The Complete Feedback Loop - Level 2 Achieved/315. submit-vertex.yml 2.1 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/03_cloud_pipeline/github/workflows/submit-vertex.yml 2.1 KB
~Get Your Files Here !/5 - Lesson 1.5 – Case Study Deep Dive/production-grade-dl-pipelines/gitignore 635 bytes
~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/Dockerfile 616 bytes
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~Get Your Files Here !/27 - Lesson 7.1 – From LocalDagRunner to Vertex AI Pipelines/03_cloud_pipeline/req.json 570 bytes
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