Artificial Intelligence Deep Learning Machine Learning TutorialsA 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.
Gcc NmfReal-time GCC-NMF Blind Speech Separation and Enhancement
Rfm AnalysisPython script (and IPython notebook) to perform RFM analysis from customer purchase history data
SqlcellSQLCell 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.
IpytestPytest in IPython notebooks.
Ipytracer 📊 Algorithm Visualizer for IPython/Jupyter Notebook
Dive Into Machine LearningDive into Machine Learning with Python Jupyter notebook and scikit-learn! First posted in 2016, maintained as of 2021. Pull requests welcome.
Spark Py NotebooksApache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Sci PypeA 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.
NotebooksA collection of Jupyter/IPython notebooks
Show astAn IPython notebook plugin for visualizing ASTs.
TelepythTelegram notification with IPython magics.
Ipynotebook machinelearningThis contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
Nbstripoutstrip output from Jupyter and IPython notebooks
Kaggle TitanicA 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.
NilmtkNon-Intrusive Load Monitoring Toolkit (nilmtk)
NbvalA py.test plugin to validate Jupyter notebooks
NumpileA tiny 1000 line LLVM-based numeric specializer for scientific Python code.
nbtopIPython Notebook server monitor inspired by htop
05 Python FilesPython 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 …
pytest-notebookA pytest plugin for regression testing and regenerating Jupyter Notebooks
HDR-imagingAn implementation of "Paul E. Debevec, Jitendra Malik, Recovering High Dynamic Range Radiance Maps from Photographs, SIGGRAPH 1997."
07 Python Advanced TopicsYou'll learn about Iterators, Generators, Closure, Decorators, Property, and RegEx in detail with examples.
03 Python Flow ControlFlow 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
GemelloNo description or website provided.
itikzCell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks
Python Computer Vision from ScratchThis 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…
my euCode and data for myeu.uk - find out what the EU has done for your area
nbmergeA tool to merge / concatenate Jupyter (IPython) notebooks
11 Python Matplotlib ModuleMatplotlib 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 …
rkThe remote Jupyter kernel/kernels administration utility