learnthings
← All paths

Machine learning, explained then built

StatQuest for the concepts, scikit-learn for the practice, 3Blue1Brown for the intuition, and Karpathy when you are ready to write the network yourself.

62 sources·13 rooms

Published by learnthings · 2h ago

machine learningdata scienceai
You get your own copy — yours to change, and to take notes on.

Stage 1 · What the field actually is

video

Fundamentals: validation, error, bias and variance

5
  1. 1A Gentle Introduction to Machine Learningyoutube.com
  2. 2Machine Learning Fundamentals: Cross Validationyoutube.com
  3. 3Machine Learning Fundamentals: The Confusion Matrixyoutube.com
  4. 4Machine Learning Fundamentals: Sensitivity and Specificityyoutube.com
  5. 5Machine Learning Fundamentals: Bias and Varianceyoutube.com
read

Two things worth reading before any modelling

2
  1. 6Google's Machine Learning Crash Coursedevelopers.google.com
  2. 7Rules of Machine Learning — engineering practice, not mathsdevelopers.google.com

Stage 2 · Regression, classification, regularisation

video

From fitting a line to logistic regression

9
  1. 8The Main Ideas of Fitting a Line to Data (The Main Ideas of Least Squares and Linear Regression.)youtube.com
  2. 9Linear Regression, Clearly Explained!!!youtube.com
  3. 10Multiple Regression, Clearly Explained!!!youtube.com
  4. 11StatQuest: Logistic Regressionyoutube.com
  5. 12Logistic Regression Details Pt1: Coefficientsyoutube.com
  6. 13ROC and AUC, Clearly Explained!youtube.com
  7. 14Regularization Part 1: Ridge (L2) Regressionyoutube.com
  8. 15Regularization Part 2: Lasso (L1) Regressionyoutube.com
  9. 16Ridge vs Lasso Regression, Visualized!!!youtube.com
read

The library and the standard textbook

3
  1. 17scikit-learn, getting startedscikit-learn.org
  2. 18Cross-validation, in the scikit-learn docsscikit-learn.org
  3. 19An Introduction to Statistical Learning (free PDF)statlearning.com

Stage 3 · Trees, ensembles, clustering, dimensions

video

The algorithms you will actually reach for

12
  1. 20StatQuest: Principal Component Analysis (PCA), Step-by-Stepyoutube.com
  2. 21StatQuest: PCA main ideas in only 5 minutes!!!youtube.com
  3. 22StatQuest: t-SNE, Clearly Explainedyoutube.com
  4. 23StatQuest: Hierarchical Clusteringyoutube.com
  5. 24StatQuest: K-means clusteringyoutube.com
  6. 25StatQuest: K-nearest neighbors, Clearly Explainedyoutube.com
  7. 26Naive Bayes, Clearly Explained!!!youtube.com
  8. 27Decision and Classification Trees, Clearly Explained!!!youtube.com
  9. 28Regression Trees, Clearly Explained!!!youtube.com
  10. 29StatQuest: Random Forests Part 1 - Building, Using and Evaluatingyoutube.com
  11. 30StatQuest: Random Forests Part 2: Missing data and clusteringyoutube.com
  12. 31AdaBoost, Clearly Explainedyoutube.com
read

Practice on real data

2
  1. 32Kaggle's Intro to Machine Learningkaggle.com
  2. 33MLU-Explain — visual explanations of the same ideasmlu-explain.github.io

Stage 4 · Neural networks, intuition then code

video

What a network is, and how it learns

4
  1. 34But what is a neural network? | Deep learning chapter 1youtube.com
  2. 35Gradient descent, how neural networks learn | Deep Learning Chapter 2youtube.com
  3. 36Backpropagation, intuitively | Deep Learning Chapter 3youtube.com
  4. 37Backpropagation calculus | Deep Learning Chapter 4youtube.com
video

Gradient descent and backpropagation, statistically

9
  1. 38The Chain Rule, Clearly Explained!!!youtube.com
  2. 39Gradient Descent, Step-by-Stepyoutube.com
  3. 40Stochastic Gradient Descent, Clearly Explained!!!youtube.com
  4. 41Happy Halloween (Neural Networks Are Not Scary)youtube.com
  5. 42The Essential Main Ideas of Neural Networksyoutube.com
  6. 43The Chain Rule, Clearly Explained!!!youtube.com
  7. 44Gradient Descent, Step-by-Stepyoutube.com
  8. 45Neural Networks Pt. 2: Backpropagation Main Ideasyoutube.com
  9. 46Backpropagation Details Pt. 1: Optimizing 3 parameters simultaneously.youtube.com
video

Build one yourself (Andrej Karpathy)

4
  1. 47The spelled-out intro to neural networks and backpropagation: building microgradyoutube.com
  2. 48The spelled-out intro to language modeling: building makemoreyoutube.com
  3. 49Building makemore Part 2: MLPyoutube.com
  4. 50Let's build GPT: from scratch, in code, spelled out.youtube.com
read

Where to go when you want to train real things

3
  1. 51Practical Deep Learning for Coders (fast.ai)course.fast.ai
  2. 52Dive into Deep Learning — free interactive bookd2l.ai
  3. 53A Recipe for Training Neural Networkskarpathy.github.io

Stage 5 · Long-form courses

video

Full courses, when you want one sitting

3
  1. 54Machine Learning for Everybody – Full Courseyoutube.com
  2. 55PyTorch for Deep Learning & Machine Learning – Full Courseyoutube.com
  3. 56Scikit-Learn Course - Machine Learning in Python Tutorialyoutube.com
read

The courses these videos come from

5
  1. 57StatQuest with Josh Starmer: Machine Learning (106 videos)youtube.com
  2. 583Blue1Brown: Neural networks (10 videos)youtube.com
  3. 59Andrej Karpathy: Neural Networks: Zero to Hero (10 videos)youtube.com
  4. 60StatQuest with Josh Starmer: Neural Networks / Deep Learning (33 videos)youtube.com
  5. 61freeCodeCamp.org: Machine Learning (17 videos)youtube.com
notebook

How to use this path

1
  1. 62The honest prerequisite list
Machine learning, explained then built · learnthings