to Unsupervised Learning\
0:00 Introduction
5:03 Course Outline
9:37 What is unsupervised learning used for
15:08 Why Use Clustering
24:28 Where to get the code
29:04 Anyone Can Succeed in this Course
Clustering\
41:00 An Easy Introduction to K-Means Clustering
48:06 Hard K-Means Exercise Prompt 1
57:19 Hard K-Means Exercise 1 Solution
1:08:28 Hard K-Means Exercise Prompt 2
1:13:32 Hard K-Means Exercise 2 Solution
1:20:41 Hard K-Means Exercise Prompt 3
1:27:36 Hard K-Means Exercise 3 Solution
1:43:59 Hard K-Means Objective Theory
1:57:00 Hard K-Means Objective Code
2:02:14 Soft K-Means
2:07:56 The Soft K-Means Objective Function
2:09:36 Soft K-Means in Python Code
2:19:39 How to Pace Yourself
2:22:58 Visualizing Each Step of K-Means
2:25:17 Examples of where K-Means can fail
2:32:50 Disadvantages of K-Means Clustering
2:35:03 How to Evaluate a Clustering (Purity, Davies-Bouldin Index)
2:41:37 Using K-Means on Real Data MNIST
2:46:38 One Way to Choose K
2:51:54 K-Means Application Finding Clusters of Related Words
3:00:32 Clustering for NLP and Computer Vision Real-World Applications
3:07:30 Suggestion Box
Clustering\
3:10:34 Visual Walkthrough of Agglomerative Hierarchical Clustering
3:13:10 Agglomerative Clustering Options
3:16:49 Using Hierarchical Clustering in Python and Interpreting the Dendrogram
3:21:28 Application Evolution
3:35:28 Application Donald Trump vs. Hillary Clinton Tweets
Mixture Models (GMMs)\
3:54:03 Gaussian Mixture Model (GMM) Algorithm
4:09:34 Write a Gaussian Mixture Model in Python Code
4:28:28 Practical Issues with GMM Singular Covariance
4:37:36 Comparison between GMM and K-Means
4:41:31 Kernel Density Estimation
4:47:56 GMM vs Bayes Classifier (pt 1)
4:57:24 GMM vs Bayes Classifier (pt 2)
5:08:54 Expectation-Maximization (pt 1)
5:20:39 Expectation-Maximization (pt 2)
5:23:04 Expectation-Maximization (pt 3)
5:31:13 Future Unsupervised Learning Algorithms You Will Learn
Up Your Environment (FAQ by Student Request)\
5:32:15 Windows-Focused Environment Setup 2018
5:52:35 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
Help With Python Coding for Beginners (FAQ by Student Request)\
6:10:08 How to Code by Yourself (part 1)
6:26:03 How to Code by Yourself (part 2)
6:35:27 Proof that using Jupyter Notebook is the same as not using it
6:47:56 Python 2 vs Python 3
Learning Strategies for Machine Learning (FAQ by Student Request)\
6:52:34 How to Succeed in this Course (Long Version)
7:02:59 Is this for Beginners or Experts Academic or Practical Fast or slow-paced
7:25:03 Machine Learning and AI Prerequisite Roadmap (pt 1)
7:36:23 Machine Learning and AI Prerequisite Roadmap (pt 2)
FAQ Finale\
7:52:30 What is the Appendix
7:55:18 BONUS Where to get discount coupons and FREE deep learning material