Table of Contents
Unsupervised Learning
- What is unsupervised learning used for?
- Why Use Clustering?
K-Means Clustering
- An Easy Introduction to K-Means Clustering
- Hard K-Means: Exercise Prompt 1
- Hard K-Means: Exercise 1 Solution
- Hard K-Means: Exercise Prompt 2
- Hard K-Means: Exercise 2 Solution
- Hard K-Means: Exercise Prompt 3
- Hard K-Means: Exercise 3 Solution
- Hard K-Means Objective: Theory
- Hard K-Means Objective: Code
- Visual Walkthrough of the K-Means Clustering Algorithm (Legacy)
- Soft K-Means
- The K-Means Objective Function
- Soft K-Means in Python Code
- How to Pace Yourself
- Visualizing Each Step of K-Means
- Examples of where K-Means can fail
- Disadvantages of K-Means Clustering
- How to Evaluate a Clustering (Purity, Davies-Bouldin Index)
- Using K-Means on Real Data: MNIST
- One Way to Choose K
- K-Means Application: Finding Clusters of Related Words
- Clustering for NLP and Computer Vision: Real-World Applications
Hierarchical Clustering
- Visual Walkthrough of Agglomerative Hierarchical Clustering
- Agglomerative Clustering Options
- Using Hierarchical Clustering in Python and Interpreting the Dendrogram
- Application: Evolution
- Application: Donald Trump vs. Hillary Clinton Tweets
Gaussian Mixture Models (GMMs)
- Gaussian Mixture Model (GMM) Algorithm
- Write a Gaussian Mixture Model in Python Code
- Practical Issues with GMM
- Comparison between GMM and K-Means
- Kernel Density Estimation
- GMM vs Bayes Classifier (pt 1)
- GMM vs Bayes Classifier (pt 2)
- Expectation-Maximization (pt 1)
- Expectation-Maximization (pt 2)
- Expectation-Maximization (pt 3)
Setting Up Your Environment
- Pre-Installation Check
- Anaconda Environment Setup
- How to install Numpy, Scipy, Matplotlib, Pandas, and Tensorflow
Extra Help With Python Coding for Beginners
- How to Code Yourself (part 1)
- How to Code Yourself (part 2)
- Proof that using Jupyter Notebook is the same as not using it
- How to use Github & Extra Coding Tips (Optional)
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