Hello, and welcome to my website. In this blog post I am going to document my AI/ML journey. This project is going to take at least 1 year of hands-on experience. So, let's get started.
Table of content
- Reference
- Probability
- Statistics
- Programming
- Machine Learning
- Deep Learning
- LLM (Large Language Model)
- Roadmap
Reference
Probability
- Probability for Statistics and Data Science (Udemy - Paid)
Statistics
- Statistics for Data Science and Business Analysis (Udemy - Paid)
Programming
- Python for Data Science and Machine Learning Bootcamp (Udemy - Paid)
- Object Oriented Programming with Python - Full Course for Beginners (YouTube)
- Automate the Boring Stuff with Python By Al Sweigart (Book)
- Automate the Boring Stuff with Python Programming (Udemy - Paid)
Machine Learning
- Machine Learning A-Z: AI, Python & R + ChatGPT Prize (Udemy - Paid)
- Andrej Karpathy (Udemy - Paid)
- ML-For-Beginners (Microsoft - GitHub)
- Machine Learning for Beginners (Microsoft Developer - YouTube)
- Machine Learning Course JavaScript Drawing App (YouTube)
- Neural Networks from Scratch - P.1 Intro and Neuron Code ((sentdex - YouTube)
Deep Learning
- PyTorch for Deep Learning & Machine Learning – Full Course (YouTube)
- Deep Learning Basics: Introduction and Overview (Lex Fridman - YouTube)
LLM (Large Language Model)
- Create a Large Language Model from Scratch with Python – Tutorial (YouTube)
- Let's build GPT: from scratch, in code, spelled out. (YouTube)
Roadmap
- selfstudy-roadmap-ml-ai (GitHub)
- AI-Expert-Roadmap (GitHub)
- Learn (Kaggle)