- A very good comprehensive tutorial to learn python http://cs231n.github.io/python-numpy-tutorial/ 28 comments learnprogramming
Linking pages
- GitHub - datasciencemasters/go: The Open Source Data Science Masters https://github.com/datasciencemasters/go 203 comments
- GitHub - dibgerge/ml-coursera-python-assignments: Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions. https://github.com/dibgerge/ml-coursera-python-assignments 72 comments
- GitHub - kjaisingh/high-school-guide-to-machine-learning: Being a high schooler myself and having studied Machine Learning and Artificial Intelligence for a year now, I believe that there fails to exist a learning path in this field for High School students. This is my attempt at creating one. https://github.com/kjaisingh/high-school-guide-to-machine-learning 38 comments
- MIT 6.881 - Robotic Manipulation http://manipulation.csail.mit.edu/Fall2020/ 1 comment
- Google Colab Free GPU Tutorial. Now you can develop deep learning… | by fuat | Deep Learning Turkey | Medium https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d 0 comments
- NLP Newsletter #10 [EN]: Improving Reproducibility in ML, Privacy and Security in NLP, XTREME, Longformer, VilBERT, exBERT,… – DAIR.AI https://dair.ai/NLP_Newsletter_10_en/ 0 comments
- Demystifying pandas and numpy filtering | Eric Heydenblog http://heydenberk.com/blog/posts/demystifying-pandas-numpy-filtering/ 0 comments
- Over 150 of the Best Machine Learning, NLP, and Python Tutorials I’ve Found | by Robbie Allen | Machine Learning in Practice | Medium https://medium.com/machine-learning-in-practice/over-150-of-the-best-machine-learning-nlp-and-python-tutorials-ive-found-ffce2939bd78 0 comments
- NumPy Tutorial: Data Analysis with Python – Dataquest https://www.dataquest.io/blog/numpy-tutorial-python/ 0 comments
- Parens for Pyplot - Squid's Blog http://gigasquid.github.io/blog/2020/01/18/parens-for-pyplot/ 0 comments
- Over 200 of the Best Machine Learning, NLP, and Python Tutorials — 2018 Edition | by Robbie Allen | Machine Learning in Practice | Medium https://medium.com/machine-learning-in-practice/over-200-of-the-best-machine-learning-nlp-and-python-tutorials-2018-edition-dd8cf53cb7dc 0 comments
- GitHub - srigalibe/CS231n-Python-NumPy-Tutorial: Teaching materials for the Convolutional Neural Networks for Visual Recognition (http://cs231n.github.io/python-numpy-tutorial/) classes at Stanford https://github.com/srigalibe/CS231n-Python-NumPy-Tutorial 0 comments
- GitHub - lukaemon/Coursera-ML-AndrewNg: use numpy, scipy, and tensorflow to implement these basic ML model and learning algorithm https://github.com/icrtiou/coursera-ML 0 comments
- Parens for Pyplot - Squid's Blog https://gigasquidsoftware.com/blog/2020/01/18/parens-for-pyplot/ 0 comments
- Generating Synthetic Sequential Data using GANs | by Armando Vieira | Towards AI https://medium.com/towards-artificial-intelligence/generating-synthetic-sequential-data-using-gans-a1d67a7752ac 0 comments
- Rohan & Lenny #1: Neural Networks & The Backpropagation Algorithm, Explained | by Rohan Kapur | A Year of Artificial Intelligence https://medium.com/a-year-of-artificial-intelligence/rohan-lenny-1-neural-networks-the-backpropagation-algorithm-explained-abf4609d4f9d#.7mwcjuftn 0 comments
- Schedule | EECS 498-007 / 598-005: Deep Learning for Computer Vision https://web.eecs.umich.edu/~justincj/teaching/eecs498/WI2022/schedule.html 0 comments
Linked pages
- Sunsetting Python 2 | Python.org https://www.python.org/doc/sunset-python-2/ 1143 comments
- Matplotlib — Visualization with Python http://matplotlib.org/ 46 comments
- NumPy https://numpy.org 17 comments
- Broadcasting — NumPy v1.24 Manual http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html 6 comments
- EricsBroadcastingDoc - SciPy wiki dump http://scipy.github.io/old-wiki/pages/EricsBroadcastingDoc 0 comments
- Indexing routines — NumPy v1.24 Manual https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html 0 comments
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