Learning Machine Learning
  • About
  • Schedules
  • Meetings
  • ML Resources
  • Physics @ KU

    Want to Learn More?

    Email us below, or sign up for our meetings!

    • University of Kansas
    • Email Us
    • Sign Up Here!

    Machine Learning Resources

    Literature

    Statistics

    The Elements of Statistical Learning: Data Mining, Inference and Prediction

    When Did Bayesian Inference Become Bayesian?

    Probability Theory: The Logic of Science by E.T. Jaynes

    Deep Learning (Neural Networks)

    Deep Learning Book (HTML) (PDF)

    A practical guide to Deep Learning in 6 months

    A Beginner’s Guide To Understanding Convolutional Neural Networks (Pt. 1)

    Author of The Hundred-Page Machine Learning Book Reddit AMA

    CMS Machine Learning Hands-on Advanced Tutorials (HATS) 2019

    Reinforcement Learning

    Demystifying Deep Reinforcement Learning

    Tutorials

    Linear Regression

    Sadia’s Tutorial (7/3/19) Linear Regression Tutorial: Github area Real world example Slides

    Linear Modeling Tools Jupyter Notebook Github area

    Introduction to Linear Regression

    Deep Learning

    3Blue1Brown: But What is a Neural Network?

    Google Machine Learning Crash Course

    Google Colab (GPU capabilities)

    Tensorflow

    Keras

    Pytorch

    Building a simple Generative Adversarial Network (GAN) using Tensorflow (Depreciated)

    Generative Adversarial Network (GAN) using Keras (more recent)

    Keras Convolutional Neural Network Data Augmentation

    Reinforcement Learning

    Dino Run Tutorial

    Physics control tasks with Deep Reinforcement Learning

    Coding

    CodeAcademy

    Python

    w3schools tutorial

    Recommendation Python learning resources

    • Feed
    © 2021 Margaret Lazarovits. Powered by Jekyll & Minimal Mistakes.