Numpy Tutorial Scipyconf 2018
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Ml Tutorial Experiment | 2,352 | 5 years ago | 6 | Jupyter Notebook | ||||||
| Coding the Machine Learning Tutorial for Learning to Learn | ||||||||||
| Projectlearn Project Based Learning | 2,074 | 5 months ago | 4 | mit | JavaScript | |||||
| A curated list of project tutorials for project-based learning. | ||||||||||
| Numpy Cn | 1,817 | 6 months ago | 30 | JavaScript | ||||||
| NumPy官方中文文档（完整版） | ||||||||||
| Dask Tutorial | 1,802 | 5 months ago | 5 | bsd-3-clause | Jupyter Notebook | |||||
| Dask tutorial | ||||||||||
| Geneticalgorithmpython | 1,564 |  | 8 | 4 months ago | 57 | September 08, 2023 | 77 | bsd-3-clause | Python | |
| Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch). | ||||||||||
| Dsp Theory | 792 | a year ago | 1 | gpl-3.0 | Jupyter Notebook | |||||
| Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc. | ||||||||||
| Deep Learning Wizard | 664 | 5 months ago | 2 | mit | HTML | |||||
| Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more. | ||||||||||
| Numpycnn | 531 | 10 months ago | 3 | May 24, 2018 | 1 | Python | ||||
| Building Convolutional Neural Networks From Scratch using NumPy | ||||||||||
| Get Started With Jax | 487 | 5 months ago | 1 | mit | Jupyter Notebook | |||||
| The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem. | ||||||||||
| Numpy Tutorials | 401 | 3 months ago | 17 | other | Python | |||||
| NumPy tutorials & educational content in notebook format | ||||||||||
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