# Learning Resources

Here is a list of my favorite learning resources to help others who are searching for similar materials. My preferred method of learning is through visuals, so many of the pages I've found are great examples of teaching complex subjects using visual aids. I've tried to order the links within each section from most basic to more advanced.**Deep Learning**- Hacker's guide to Neural Networks - Andrej Karpathy
- Using neural nets to recognize handwritten digits - Michael Nielsen
- Interactive guide to Neural Networks using JavaScript
- Convolutional Neural Networks - Andrej Karpathy
- Regularization - Andrew Ng
- How the backpropagation algorithm works
- Understanding LSTMs
- Attention and Augmented Recurrent Neural Networks
- Sequence to Sequence (seq2seq) and Attention
- The Illustrated Transformer

**Statistics/Probability**- Seeing Theory: A visual introduction to probability and statistics
- Review of Probability Theory
- CS 229 Probability Review
- Geometric Interpretation of the Covariance Matrix
- Regression modelling and other methods to control confounding | Occupational & Environmental Medicine
- Variance and Bias (Variance Explained)
- Introduction to Linear Mixed Models - IDRE Stats
- Fixed effect, random effect and mixed effect models
- Introduction to EM: Gaussian Mixture Models
- CS 229 Expectation Maximization

**Linear Algebra**

**Optimization**

**Hidden Markov Models (HMMs)**