Hey!
MY QUICK UPDATES
- This past month I started a YouTube Channel, cleaned up my Personal Website, and revamped this Newsletter. My goal is to create content that helps others and myself learn about Data Science / Machine Learning / Artificial Intelligence.
- I spent a lot of time working on Kaggle Competitions, the Introduction to Statistical Learning book, and the Google Machine Learning Crash Course.
- I’ve also subscribed to a variety of other AI Newsletters that I need to make the time to read everyday.
THOUGHTS, INSIGHTS, AND ADVICE
- There is no Machine Learning resource that will teach you everything you need to know. Some are too high level, some are too mathematical, some are outdated, some have no code, etc. The only path forward is to bring awareness to your weaknesses and then find resources that target them (projects, classes, friends, videos, books, blogs, newsletters, etc.).
RANDOM LEARNINGS, KNOWLEDGE, AND REMINDERS
- The Three Main Types of Machine Learning: Supervised, Unsupervised, Reinforcement Learning
- Bias vs Variance Tradeoff: Making your Model simpler (increasing bias) makes it less capable of fitting complex data (decreasing variance). Making your Model more complex (increasing variance) makes it less capable of correctly fitting simple data (decreasing bias).
MY NEW CONTENT
OTHER USEFUL/INTERESTING RESOURCES
- If you’re trying to get into Data Science / Machine Learning and you don’t know about Kaggle… you should. Check it out! It’s free: https://www.kaggle.com/
Michael Hammer
Read all my Newsletters here: https://michaelphammer.com/newsletter/