dapopov-st / lakemaryai

LMHS AI Club

Links to Deep Learning Courses

fastai (our primary source)

fastai course website

CS230 Stanford

cs230 Stanford course website

MIT Intro to Deep Learning

MIT Intro to Deep Learning course website

Introduction to AI

Code.org

Code.org's intro to AI

Tensorflow

Tensorflow Tutorials (Hands On)

tensorflow tutorials

Machine Learning (a superset of Deep Learning and a subset of AI)

Introduction to Machine Learning for Coders (by Jeremy Howard of fastai)

Jeremy Howards's course covering random forests and deep learning foundations

Machine Learning by Stanford University (you might be able to enroll after your read the Terms with your parents)

Andrew Ng's classic on Coursera

Basic Math for ML and DL

Mathematics for Machine Learning [Full Course] | Essential Math for Machine Learning | Edureka

The Missing Semester of your CS Educations (MIT Computer Science)

An amazing resource for learning to work at the command line

https://missing.csail.mit.edu/

How Neural Networks Work

3Blue1Brown

• But what is a neural network? | Chapter 1, Deep learning](https://www.youtube.com/watch?v=aircAruvnKk)
• Gradient descent, how neural networks learn | Chapter 2, Deep learning](https://www.youtube.com/watch?v=IHZwWFHWa-w)
• What is backpropagation really doing? | Chapter 3, Deep learning](https://www.youtube.com/watch?v=Ilg3gGewQ5U)
• Backpropagation calculus | Chapter 4, Deep learning](https://www.youtube.com/watch?v=tIeHLnjs5U8)

Pytorch

Pytorch engineer https://github.com/python-engineer/pytorchTutorial

#Tnet https://github.com/dapopov-st/LakeMaryAI/blob/main/Trashnet%20fastai%20v1.py

Linux commands

The 50 Most Popular Linux & Terminal Commands

Git and Github

Git

Github

Python

A Guide to Python through the Game of Tic-Tac-Toe Part 1: Non-OOP

[A Guide to Python through the Game of Tic-Tac-Toe Part 2: OOP Forthcoming or will be merged with Part 1]

Club Constitution