mrdbourke / machine-learning-roadmap Goto Github PK

A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.

License: MIT License

machine-learning deep-learning data data-science

machine-learning-roadmap's Introduction

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:

🤔 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?
📚 Machine Learning Resources - okay, this is cool, how can I learn all of this?

See the full interactive version.

Watch a feature-length film video walkthrough (yes, really, it's longer than most movies).

Many of the materials in this roadmap were inspired by Daniel Formoso's machine learning mindmaps,so if you enjoyed this one, go and check out his. He also has a mindmap specifically for deep learning too.

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0xkoios mutaqim96 nirmalkrishnav nchkalyanbabu wloszynski abdelatifbous ramirezramirez125 rajaramkuberan upadhyatejas kharwade-aditya oracle-fab adedeji-x elizabeth37 black-hat-pikachu liyi54 dhirajbagul jprnvkumr cvpo a8hay mahabubarafat yushu-liu tonymx harshavardhanraja m-ghazi gudlaarunkumar mdfazal sriramswar debasishbiswasnj abir-reza primus-ai alomdaelmasry lalithreddy1998 joskid lyg6772 gbagade02 miatcheza eblancoh mikhailchetin duygo3003 o7s8r6 marcelomata lucaloeffler dipuo amoedorodrigo alphacentauri763 radygo itachi116 tapanhp jianliao padamshrestha shotaro-yoshinaga sodikinson lewisitor maxcodextc goutham183 cubegame3d duoduofeizhuzi quickpanda swpnl7 yxie80 wwinter500 dung1208 abhim2192 bornfreesoul devqueue vasanthgx saviodcunha vrushin haiahems thekuntalpaul hadryan nalim2 himanshurepo kk289 jaynoel hhaider15 rscool78 patrickcnkm freezesoul softcoda jeremyfrc gvc0461082002 tsachit anikeshpatel rustamsemenov mike-box nivir emiyalter daemonoj lijunnangit septianrin nikkilinliu ggarciaf surajthakur1012 mlops-aiops nawaf1195 lab4ai shobhit-agarwal randomraf pankaj-ra

machine-learning-roadmap's Issues

Additions to the machine learning roadmap 2020

It was a whole new journey going through your roadmap video, Satisfied my cravings!

Please add below if you think they are worth considering,

No mention of kaggle when you were talking about GPU, although you mentioned Colab. Kaggle offers GPU and TPU for notebooks and a lot of people use it on a daily basis.
Machine learning project documentation, design documents, project reports, etc. as another step or sub-step in the roadmap. It helps folks who want to know how real time projects and reports are documented.
Math and numbers were mentioned quite a bit, but how about statistics, it would be great if you add something on that as well.

Pls ignore if any of this is already in there or I missed while I was going through the roadmap. Thanks

Adding model optimization/quantization

Nice roadmap 👍
can you add in roadmap optimization and quantization ...

Add some links to dataset preparation tools

Hi, thank you for your project, it looks great! I noticed there are little information about dataset preparation tools in the mindmap. We're developing few of them, namely:

CVAT, a famous open source Computer Vision annotation tool
Datumaro, a dataset management tool and a library

I think, such kind of information might be useful for readers.