The 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
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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
Parallel computing with task scheduling
An open access book on scientific visualization using python and matplotlib
Open Machine Learning Course
Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
Fast data visualization and GUI tools for scientific / engineering applications
N-D labeled arrays and datasets in Python
A python module for scientific analysis of 3D data based on VTK and Numpy
Fast NumPy array functions written in C
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Read and write Neuroglancer datasets programmatically.