There are 707 repositories under numpy topic.
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Python Data Science Handbook: full text in Jupyter Notebooks
Visualizer for neural network, deep learning and machine learning models
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
机器学习相关教程
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
An open access book on scientific visualization using python and matplotlib
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Open Machine Learning Course
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
《利用Python进行数据分析·第2版》
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Repository to store sample python programs for python learning
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
Technical Analysis Library using Pandas and Numpy
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Fast data visualization and GUI tools for scientific / engineering applications