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| Archived
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1 - Introduction\02 - Getting Started with Google Cloud Platform and Qwiklabs.mp4
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1 - Introduction\01 - Introduction.mp4
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2 - Practical ML\08 - Short history of ML - Neural Networks.mp4
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2 - Practical ML\09 - Short history of ML - Decision Trees.mp4
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2 - Practical ML\05 - Regression and Classification.mp4
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2 - Practical ML\03 - Introduction to Practical ML.mp4
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2 - Practical ML\12 - Short history of ML - Modern Neural Networks.mp4
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2 - Practical ML\04 - Supervised Learning.mp4
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2 - Practical ML\11 - Short history of ML - Random Forests.mp4
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2 - Practical ML\06 - Short history of ML - Linear Regression.mp4
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2 - Practical ML\10 - Short history of ML - Kernel Methods.mp4
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2 - Practical ML\07 - Short history of ML - Perceptron.mp4
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4 - Generalization and Sampling\26 - Introduction to Generalization and Sampling.mp4
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4 - Generalization and Sampling\35 - [ML on GCP C2] Exploring and Creating ML Datasets.mp4
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4 - Generalization and Sampling\30 - Demo - Creating Repeatable Samples in BigQuery.mp4
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4 - Generalization and Sampling\36 - Lab Solution - Exploring and Creating ML Datasets.mp4
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4 - Generalization and Sampling\33 - Lab Solution - Creating Repeatable Dataset Splits.mp4
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4 - Generalization and Sampling\31 - Lab Intro - Creating Repeatable Dataset Splits.mp4
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4 - Generalization and Sampling\28 - When to Stop Model Training.mp4
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4 - Generalization and Sampling\29 - Creating Repeatable Samples in BigQuery.mp4
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4 - Generalization and Sampling\34 - Lab Intro - Exploring and Creating ML Datasets.mp4
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4 - Generalization and Sampling\27 - Generalization and ML Models.mp4
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4 - Generalization and Sampling\32 - [ML on GCP C2] Creating repeatable splits in BigQuery.mp4
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3 - Optimization\13 - Introduction to Optimization.mp4
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3 - Optimization\21 - Activity - TensorFlow Playground - Advanced.mp4
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3 - Optimization\23 - Activity - Loss Curve Troubleshooting.mp4
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3 - Optimization\18 - Troubleshooting a Loss Curve.mp4
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3 - Optimization\15 - Introducing the Course Dataset.mp4
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3 - Optimization\25 - Confusion Matrix.mp4
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3 - Optimization\16 - Introducing Loss Functions.mp4
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3 - Optimization\17 - Gradient Descent.mp4
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3 - Optimization\19 - ML Model Pitfalls.mp4
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3 - Optimization\20 - Activity - Introducing the TensorFlow Playground.mp4
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3 - Optimization\14 - Defining ML Models.mp4
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3 - Optimization\22 - Activity - Practicing with Neural Networks.mp4
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3 - Optimization\24 - Performance Metrics.mp4
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5 - Summary\37 - Summary.mp4
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