Learning... Machine Learning
Introduction
At the time of writing this post, I have just a little understanding in machine learning. I did some basic ANN with Keras and learned how to use a little bit of pandas.
This post is a planning and resource page for my machine learning journey and projects.
Here is a list of things I want to explore in the field of ML
- Web scrapping for ML
- Image classification (with CNNs)
- Reinforcement learning, customize environments (with DQN)
- OpenAI API
- Stream lit web tool scripting
Some useful tools to learn:
- stream lit: Create web apps very quickly. This is useful for prototyping ideas and developing projects
Learning resources and project tutorials for each of these topics are detailed below. I will have separate posts when I explore each of these topics. Yes, this is the "planning stage".
Expectations
- Spend a minimum of 5 hours every week
- Improve the learning process
- Improve expression ability, explain concepts as I learn
Some good tutors in these areas
codebasics: codebasics - YouTube
- Good basics tutorials in data science and machine learning
林亦LYi: 林亦LYi的个人空间_哔哩哔哩_bilibili
- Interesting projects (with GitHub source) with RL -> "林亦的游戏AI合集"
Nicholas Renotte: (1) Nicholas Renotte - YouTube
- Lots of projects with GitHub source. Not so good teaching, and code often have errors.
Web scrapping for ML
Learning resources:
Project:
Stream lit web tool scripting
Learning resources:
Project:
Image classification
Learning resources:
Episode 22-32 (1) Introduction | Deep Learning Tutorial 1 (Tensorflow Tutorial, Keras & Python) - YouTube