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| Archived
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7 - Custom Estimator\42 - Keras Models.mp4
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7 - Custom Estimator\43 - Demo of Keras + Estimator.mp4
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7 - Custom Estimator\38 - Custom Estimator.mp4
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7 - Custom Estimator\40 - Lab Intro- Implementing a Custom Estimator.mp4
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7 - Custom Estimator\39 - Model Function.mp4
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7 - Custom Estimator\41 - [ML on GCP C5] Using Custom Estimators.mp4
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5 - The Science of Neural Networks\27 - Training Neural Networks.mp4
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5 - The Science of Neural Networks\29 - [ML on GCP C5] Using Neural Networks to build ML model.mp4
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5 - The Science of Neural Networks\26 - Lab Intro - Neural Networks Playground.mp4
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5 - The Science of Neural Networks\28 - Lab Intro - Using Neural Networks to build a ML Model.mp4
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5 - The Science of Neural Networks\25 - Neural Networks.mp4
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5 - The Science of Neural Networks\24 - Introduction.mp4
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5 - The Science of Neural Networks\30 - Multi-class Neural Networks.mp4
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3 - Hyperparameter Tuning\13 - Introduction.mp4
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3 - Hyperparameter Tuning\15 - Think Beyond Grid Search.mp4
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3 - Hyperparameter Tuning\16 - Lab Intro - Improve Model Accuracy by Hyperparameter Tuning with Cloud MLE.mp4
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3 - Hyperparameter Tuning\17 - [ML on GCP C5] Improve model accuracy by hyperparameter tuning with Cloud MLE.mp4
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3 - Hyperparameter Tuning\14 - Parameters vs Hyperparameters.mp4
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3 - Hyperparameter Tuning\18 - Lab Solution - Improve Model Accuracy by Hyperparameter Tuning with Cloud MLE.mp4
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art-science-ml.zip |
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6 - Embeddings\35 - Sparse Tensors.mp4
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6 - Embeddings\37 - Similarity Property.mp4
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6 - Embeddings\33 - Recommendations.mp4
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6 - Embeddings\36 - Train an Embedding.mp4
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6 - Embeddings\34 - Data-driven Embeddings.mp4
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6 - Embeddings\31 - Intro to Embeddings.mp4
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6 - Embeddings\32 - Review of Embeddings.mp4
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4 - A Pinch of Science\20 - Regularization for Sparsity.mp4
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4 - A Pinch of Science\22 - Lab Solution - L1 Regularization.mp4
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4 - A Pinch of Science\21 - Lab Intro - L1 Regularization.mp4
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4 - A Pinch of Science\23 - Logistic Regression.mp4
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4 - A Pinch of Science\19 - Introduction.mp4
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8 - Summary\44 - Summary.mp4
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8 - Summary\45 - Specialization Summary.mp4
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1 - Introduction\01 - Introduction.mp4
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2 - The Art of ML\10 - Lab Intro - Hand-Tuning ML Models.mp4
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2 - The Art of ML\05 - Lab Intro - Regularization.mp4
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2 - The Art of ML\09 - Practicing with Tensorflow Code.mp4
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2 - The Art of ML\08 - Optimization.mp4
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2 - The Art of ML\12 - Lab Solution - Hand-Tuning ML Models.mp4
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2 - The Art of ML\03 - Regularization.mp4
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2 - The Art of ML\07 - Learning Rate and Batch Size.mp4
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2 - The Art of ML\04 - L1 & L2 Regularizations.mp4
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2 - The Art of ML\02 - Introduction.mp4
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2 - The Art of ML\11 - [ML on GCP C5] Improve model accuracy by hand-tuning hyperparameters.mp4
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2 - The Art of ML\06 - Lab Solution - Regularization.mp4
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