A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
Namely:
- 🤔 Machine Learning Problems - what does a machine learning problem look like?
- ♻️ Machine Learning Process - once you’ve found a problem, what steps might you take to solve it?
- 🛠 Machine Learning Tools - what should you use to build your solution?
- 🧮 Machine Learning Mathematics - what exactly is happening under the hood of all the machine learning code you're writing?
- 📚 Machines Learning Resources - okay, this is cool, how can I learn all of this?
See the full interactive version.