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👾 my old deep learning notebooks (e.g., tensorflow examples, caffee, deep art, numpy)
| airflow | ||
| data-engineering | ||
| deep_art | ||
| dockerfiles | ||
| ml_notebooks | ||
| numpy_examples | ||
| tensorflow_examples | ||
| .gitignore | ||
| README.md | ||
🤖 [Scrath Space] Machine Learning & Deep Learning projects and resources
- My ML Jupyter notebooks: lots of experiments
- Tensorflow: learning examples
- DeepArt: deep learning generated art
- ML Notebooks: jupyter notebooks with ML examples
- Numpy: my code and examples using Numpy
- Data Engineering: resources for deployment
Learning Resources
- Energy-based Approaches to Representation Learning - Yann LeCun.
- Stanford's Machine Learning Course.
- Google's Developer Machine Learning Course.
- Deep Learning Lectures by Lex Fridman.
- Andrew Ng's deeplearning.ai
- A Chart of Neural Networks.
- UCL Course on RL
- Stanford's Convolutional Neural Networks for Visual Recognition
- The 9 CNN Papers You Need To Know About.
- NVIDIA Deep Learning Course
- DeepBench.
- Deep Fake source code.
- Deep Learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville.
- Tensorflow plaground.
- Google's Tensorflow courses.
- MIT Deep Learning Basics.