ML Roadmap 2023

1. Programação

1.1 Python

Microsoft - Python para iniciantes

Coursera - Programming for Everybody (Getting Started with Python)

freeCodeCamp.org - Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)

Python Exercises, Practice, Solution

1.1.1 Numpy

Github - NumPy tutorials

Livro - Guide to NumPy

NumPy Exercises, Practice, Solution

1.1.2 Pandas

Livro - Learning pandas eBook (PDF)

Kaggle - Learn Pandas

Pandas Exercises, Practice, Solution

1.1.3 Matplotlib

Matplotlib tutorial for beginners

Livro - Matplotlib

Matplotlib: - Exercises, Practice, Solution

1.1.4 Seaborn

freeCodeCamp.org Seaborn Tutorial: Seaborn Full Course

Seaborn Exercises

2. Machine Learning

2.1 Cursos

Coursera - Machine Learning Specialization

fast.ai - Practical Deep Learning for Coders 2022

MIT - Introduction to Machine Learning

fast.ai

2.2 Textos

Livro - Pattern Recognition and Machine Learning - Christopher Bishop

Notebooks - fast.ai fastbook

Livro - Neural Networks and Deep Learning

Livro - Deep Learning with Python

Livro - Deep Learning

Youtube - Deep Learning Book Club

Livro - A Course in Machine Learning

Livro - Introduction to Machine Learning

Online - Dive into Deep Learning

Livro - An Introduction to Statistical Learning

Livro - The Elements of Statistical Learning

Livro - Reinforcement Learning: An Introduction

3. Evoluindo

Kaggle

Papers With Code

ArXiv

AI Pub

Papers Daily

From 0.1 to 0.0001

Referência - Matemática

Mathematics for Machine Learning

Khan Academy - Linear Algebra

Khan Academy - Statistics Probability

Linear Algebra - Jim Hefferon

The Matrix Cookbook

Calculus Made Easy, by Silvanus Thompson

Think Stats Probability and Statistics for Programmers

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