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04. Introduction to Optimisation and the Gradient Descent Algorithm/08. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 305.5 MB
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05. Predict House Prices with Multivariable Linear Regression/32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 256.0 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/10. Understanding the Learning Rate.mp4 248.1 MB
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03. Python Programming for Data Science and Machine Learning/10. [Python] - Module Imports.mp4 243.3 MB
12. Serving a Tensorflow Model through a Website/14. Calculating the Centre of Mass and Shifting the Image.mp4 234.1 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/09. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 229.6 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/10. Use the Model to Make Predictions.mp4 228.9 MB
05. Predict House Prices with Multivariable Linear Regression/14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 224.8 MB
11. Use Tensorflow to Classify Handwritten Digits/12. Different Model Architectures Experimenting with Dropout.mp4 224.1 MB
08. Test and Evaluate a Naive Bayes Classifier Part 3/06. Visualising the Decision Boundary.mp4 215.3 MB
08. Test and Evaluate a Naive Bayes Classifier Part 3/11. A Naive Bayes Implementation using SciKit Learn.mp4 204.6 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/11. How to Create 3-Dimensional Charts.mp4 202.9 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/09. Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 200.8 MB
12. Serving a Tensorflow Model through a Website/07. Loading a Tensorflow.js Model and Starting your own Server.mp4 197.2 MB
12. Serving a Tensorflow Model through a Website/09. Styling an HTML Canvas.mp4 196.5 MB
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