Artificial Intelligence Deep Learning Machine Learning Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Real-time GCC-NMF Blind Speech Separation and Enhancement
Python script (and IPython notebook) to perform RFM analysis from customer purchase history data
SQLCell is a magic function for the Jupyter Notebook that executes raw, parallel, parameterized SQL queries with the ability to accept Python values as parameters and assign output data to Python variables while concurrently running Python code. And *much* more.
Pytest in IPython notebooks.
📊 Algorithm Visualizer for IPython/Jupyter Notebook
Dive Into Machine Learning
Dive into Machine Learning with Python Jupyter notebook and scikit-learn! First posted in 2016, maintained as of 2021. Pull requests welcome.
Spark Py Notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.
A collection of Jupyter/IPython notebooks
An IPython notebook plugin for visualizing ASTs.
Telegram notification with IPython magics.
This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
strip output from Jupyter and IPython notebooks
A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.
Non-Intrusive Load Monitoring Toolkit (nilmtk)
A py.test plugin to validate Jupyter notebooks
A tiny 1000 line LLVM-based numeric specializer for scientific Python code.
IPython Notebook server monitor inspired by htop
05 Python Files
Python too supports file handling and allows users to handle files i.e., to read and write files, along with many other file handling options, to operate on files. The concept of file handling has stretched over various other languages, but the implementation is either complicated or lengthy, but like other concepts of Python, this concept here …
A pytest plugin for regression testing and regenerating Jupyter Notebooks
An implementation of "Paul E. Debevec, Jitendra Malik, Recovering High Dynamic Range Radiance Maps from Photographs, SIGGRAPH 1997."
07 Python Advanced Topics
You'll learn about Iterators, Generators, Closure, Decorators, Property, and RegEx in detail with examples.
03 Python Flow Control
Flow control is the order in which statements or blocks of code are executed at runtime based on a condition. Learn Conditional statements, Iterative statements, and Transfer statements
No description or website provided.
Cell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks
Python Computer Vision from Scratch
This repository explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply…
Code and data for myeu.uk - find out what the EU has done for your area
A tool to merge / concatenate Jupyter (IPython) notebooks
11 Python Matplotlib Module
Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. It was introduced by John Hunter in the year 2002. One of the greatest benefits of visualization is that it allows us visual access to …
The remote Jupyter kernel/kernels administration utility