机器学习的学习路线图项目

# 2020 Machine Learning Roadmap (still 90% valid for 2023)  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: 1. 🤔 **Machine Learning Problems** - what does a machine learning problem look like? 2. ♻️ **Machine Learning Process** - once you’ve found a problem, what steps might you take to solve it? 3. 🛠 **Machine Learning Tools** - what should you use to build your solution? 4. 🧮 **Machine Learning Mathematics** - what exactly is happening under the hood of all the machine learning code you're writing? 5. 📚 **Machine Learning Resources** - okay, this is cool, how can I learn all of this? See the [full interactive version](https://dbourke.link/mlmap). [Watch a feature-length film video walkthrough](https://youtu.be/pHiMN_gy9mk) (yes, really, it's longer than most movies). Many of the materials in this roadmap were inspired by [Daniel Formoso](https://github.com/dformoso)'s [machine learning mindmaps](https://github.com/dformoso/machine-learning-mindmap),so if you enjoyed this one, go and check out his. He also has a mindmap specifically for [deep learning](https://github.com/dformoso/deeplearning-mindmap) too.