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Outline and Motivation
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Where to get the Code and Data
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All Data is the Same
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Plug-and-Play
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Bias-Variance Key Terms
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Bias-Variance Decomposition
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Polynomial Regression Demo
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K-Nearest Neighbor and Decision Tree Demo
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Cross-Validation as a Method for Optimizing Model Complexity
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Bootstrap Estimation
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Bootstrap Demo
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Bagging
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Bagging Regression Trees
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Bagging Classification Trees
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Stacking
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Random Forest Algorithm
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Random Forest Regressor
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Random Forest Classifier
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Random Forest vs Bagging Trees
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Implementing a "Not as Random" Forest
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Connection to Deep Learning: Dropout
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AdaBoost Loss Function: Exponential Loss
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Comparison to Stacking
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Connection to Deep Learning
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Summary and What's Next
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What is the Appendix?
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Confidence Intervals
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Windows-Focused Environment Setup 2018
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How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
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How to Code by Yourself (part 1)
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How to Code by Yourself (part 2)
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How to Succeed in this Course (Long Version)
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Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
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Proof that using Jupyter Notebook is the same as not using it
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BONUS: Where to get Udemy coupons and FREE deep learning material
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Python 2 vs Python 3
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What order should I take your courses in? (part 1)
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What order should I take your courses in? (part 2)