Building Deep Learning Models on Databricks

Files Included :

01 Quick Overview of TensorFlow and Keras.mp4 (5.57 MB)
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02 Demo - Setting up the Databricks Environment.mp4 (10.79 MB)
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03 Demo - Exploring and Preprocessing Data.mp4 (11.76 MB)
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04 Demo - Training a Regression Model Using TensorFlow.mp4 (8.8 MB)
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05 Demo - Autologging Model Parameters.mp4 (17.13 MB)
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06 Demo - Comparing Multiple Model Runs.mp4 (12.43 MB)
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07 Demo - Using Bamboolib for Loading and Exploring Data.mp4 (13.02 MB)
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08 Demo - Data Cleaning Using Bamboolib - I.mp4 (13.58 MB)
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09 Demo - Data Cleaning Using Bamboolib - II.mp4 (13.82 MB)
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10 Demo - Preprocessing Data for Deep Learning.mp4 (6.94 MB)
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11 Demo - Training Multiple Models Using Multiple Runs.mp4 (13.49 MB)
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12 Demo - Registering Models and Specifying Stages.mp4 (5.17 MB)
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13 Demo - Creating a Delta Table for Batch Inference.mp4 (5.33 MB)
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14 Demo - Using Model for Batch Inference.mp4 (11.91 MB)
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1 Course Overview.mp4 (3.6 MB)
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1 Prerequisites and Course Outline.mp4 (3.53 MB)
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2 The Databricks Machine Learning Runtime.mp4 (11.11 MB)
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3 Introducing MLflow.mp4 (11.69 MB)
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1 A Quick Overview of PyTorch.mp4 (5.85 MB)
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2 Demo - Preprocessing Data for Classification.mp4 (10.49 MB)
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3 Demo - Training a PyTorch Model Using MLflow Tracking.mp4 (18.9 MB)
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4 Demo - Use Classic Serving to Serve Model Predictions.mp4 (16.55 MB)
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5 Demo - Loading Image Data for Classification.mp4 (6.78 MB)
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6 Demo - Training a PyTorch Image Classification Model.mp4 (10.69 MB)
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7 Horovod for Distributed Training.mp4 (4.87 MB)
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8 Demo - Setting up Functions for Single Node Training.mp4 (17.28 MB)
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9 Demo - Performing Distributed Training Using the Horovod Runner.mp4 (13.35 MB)
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1 Understanding Hyperparameters.mp4 (3.19 MB)
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2 Hyperopt for Hyperparameter Tuning.mp4 (8.29 MB)
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3 Demo - Hyperparameter Tuning Using Hyperopt.mp4 (17.64 MB)
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4 Demo - Training the Model with the Best Parameters.mp4 (14.39 MB)
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5 Summary and Further Study.mp4 (1.6 MB)
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