99-ML-Learning-Projects
A list of 99 machine learning projects for anyone interested to learn from coding and building projects (by gimseng)
d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. (by d2l-ai)
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| 99-ML-Learning-Projects | d2l-en | |
|---|---|---|
| 1 | 6 | |
| 555 | 21,564 | |
| - | 2.8% | |
| 0.0 | 8.7 | |
| 2 months ago | about 1 month ago | |
| Jupyter Notebook | Python | |
| MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
99-ML-Learning-Projects
Posts with mentions or reviews of 99-ML-Learning-Projects.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-30.
-
I created a way to learn machine learning through Jupyter
Looks cool. Also sounds like it would fit will with the 99 ML Projects repo. Maybe you could contribute here https://github.com/gimseng/99-ML-Learning-Projects
d2l-en
Posts with mentions or reviews of d2l-en.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-10.
- which book to chose for deep learning :lan Goodfellow or francois chollet
- d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
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How to pre-train BERT on different objective tasks using HuggingFace
There might is bert library for pre-train bert model in huggingface, But I suggestion that you train bert model in native pytorch to understand detail, Limu's course is recommended for you
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The Transformer in Machine Translation
GitHub's article on Dive into Deep Learning
- D2l-En
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I created a way to learn machine learning through Jupyter
There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
What are some alternatives?
When comparing 99-ML-Learning-Projects and d2l-en you can also consider the following projects:
PySyft - Perform data science on data that remains in someone else's server
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images