Repository to store sample python programs for python learning

Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.

Grokking Deep Reinforcement Learning

中文版scipy-lecture-notes. 网站下线, 以离线HTML的形式继续更新, 见release.

Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, Numpy can also be used as an efficient multi-dimensional container of generic data.

Source material for Python Like You Mean it

Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera

Implementation of the generalized 2D convolution with dilation from scratch in Python and NumPy

Deep learning library in python from scratch

Notes & Code to go over "Grokking Deep Learning" Book by Andrew Trask

This repository contains jupyter notebook and other resources made by me during learning Data Science

Cheat Sheet generated in the Introduction to NumPy course

Python tutorials in markdown format. These tutorials look at installation on Python and Python IDEs, object orientated programming, the object orientated design pattern known as the Python data model, the concept of inheritance and how the data model is extended for text, numeric and collection based builtins classes and the numeric Python stack.

NumPy fundamentals for tensor computation; Matplotlib for data visualization

Repository for participants of the "Scientific Python" training

Basics of ML libraries Explained through Jupyter Notebooks

We design this course with 9 lessons to help beginners can quickly understand and utilize this useful library.

Basic Python learning - notebooks

A Numpy Tutorial for Beginners