| anthony-wang/BestPractices |
142 |
|
0 |
0 |
over 2 years ago |
0 |
|
6 |
mit |
Jupyter Notebook |
| Things that you should (and should not) do in your Materials Informatics research. |
| MyLtYkRiTiK/dl_in_nlp_2019 |
102 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
|
Python |
| Taking together Stanford cs224n course with support of iPavlov team. |
| JannesKlaas/MLiFC |
87 |
|
0 |
0 |
about 8 years ago |
0 |
|
12 |
mit |
Jupyter Notebook |
| Course Material for the machine learning in financial context bootcamp |
| rexlow/AI-Reading-Materials |
77 |
|
0 |
0 |
over 5 years ago |
0 |
|
1 |
mit |
|
| Some of the ML and DL related reading materials, research papers that I've read |
| Tony-Y/cgnn |
75 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| Crystal Graph Neural Networks |
| dphi-official/Deep_Learning_Bootcamp |
67 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| All the learning material for deep learning bootcamp can be found in this repository |
| anthony-wang/CrabNet |
65 |
|
0 |
0 |
almost 3 years ago |
0 |
|
14 |
mit |
Python |
| Predict materials properties using only the composition information! |
| huzongxiang/MatDGL |
63 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
bsd-2-clause |
Python |
| MatDGL is a neural network package that allows researchers to train custom models for crystal modeling tasks. It aims to accelerate the research and application of material science. |
| holbertonschool/deep-learning |
49 |
|
0 |
0 |
almost 10 years ago |
0 |
|
0 |
|
HTML |
| CornellDataScience/Deep-Learning-Course |
20 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
mit |
Python |
| Course material for introduction to deep learning in TensorFlow |
