Displaying 1 to 20 from 30 results

Data-Analysis-and-Machine-Learning-Projects - Repository of teaching materials, code, and data for my data analysis and machine learning projects

  •    Jupyter

This is a repository of teaching materials, code, and data for my data analysis and machine learning projects.Each repository will (usually) correspond to one of the blog posts on my web site.

spark-py-notebooks - Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

  •    Jupyter

This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, from basic to advanced, by using the Python language. If Python is not your language, and it is R, you may want to have a look at our R on Apache Spark (SparkR) notebooks instead. Additionally, if your are interested in being introduced to some basic Data Science Engineering, you might find these series of tutorials interesting. There we explain different concepts and applications using Python and R.

dive-into-machine-learning - Dive into Machine Learning with Python Jupyter notebook and scikit-learn!


I learned Python by hacking first, and getting serious later. I wanted to do this with Machine Learning. If this is your style, join me in getting a bit ahead of yourself. I suggest you get your feet wet ASAP. You'll boost your confidence.

musicinformationretrieval.com - Instructional notebooks on music information retrieval.

  •    Jupyter

stanford-mir is now musicinformationretrieval.com. This repository contains instructional Jupyter notebooks related to music information retrieval (MIR). Inside these notebooks are Python code snippets that illustrate basic MIR systems.

Machine-Learning / Deep-Learning / AI + Web3 -Tutorials

  •    Python

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.

nbstripout - strip output from Jupyter and IPython notebooks

  •    Python

Opens a notebook, strips its output, and writes the outputless version to the original file. Useful mainly as a git filter or pre-commit hook for users who don't want to track output in VCS.

Python-Lectures - IPython Notebooks to learn Python

  •    Jupyter

Python is a modern, robust, high level programming language. It is very easy to pick up even if you are completely new to programming. Mac OS X and Linux comes pre installed with python. Windows users can download python from https://www.python.org/downloads/ .

vscodeJupyter - Jupyter for Visual Studio Code

  •    TypeScript

For further information and details continue through to the documentation.

relevant-search-book - Code and Examples for Relevant Search

  •    Jupyter

Code and Examples for Relevant Search by Doug Turnbull and John Berryman. Published by Manning Publications.Examples for this book are written in Python 2.7 and use iPython notebook. The first thing you'll need to do is install Python, pip (the Python package installer).

nbmerge - A tool to merge / concatenate Jupyter (IPython) notebooks

  •    Python

Alternatively, nbmerge can cursively collect all files in the current directory and below, recursively. After collection, it sorts them lexicographically. You can use a regular expression as a file name predicate. All .ipynb_checkpoints are automatically ignored. And, you can use the -i option to ignore any notebook prefixed with an underscore (think pseudo-private in python). Finally, you can also instruct the script to demarcate the boundary between each original file with the -b / -boundary [BOUNDARY] flag. The src_nb value in the metadata for the first cell in each original notebook will then contain the path of the original notebook, relative to the cwd at the point of script execution.

Sentiment-Classification-Example - IPython Notebook for Sentiment Classification

  •    Python

This IPython Notebook provides a complete example of what a notebook could look like for data science.

scipy-cookbook - Scipy Cookbook

  •    Jupyter

This is a conversion and second life of SciPy Cookbook (previously at http://wiki.scipy.org/Cookbook/); as a bunch of Ipython notebooks. Alternatively open an issue and attach (drag-and-drop) a fixed notebook file.

numpile - A tiny 1000 line LLVM-based numeric specializer for scientific Python code.

  •    Jupyter

A tiny 1000 line LLVM-based numeric specializer for scientific Python code. You really shouldn't use this for anything serious, it's just to demonstrate how you might build one of these things from scratch. There's a lot of untapped potential and low hanging fruit around selective embedded JIT specialization for array expression languages in the SciPython space.

evolutionary-computation-course - Jupyter/IPython notebooks about evolutionary computation.

  •    Jupyter

This repository contains the Jupyter/IPython notebooks used in the demonstration classes of my course "Advanced Evolutionary Computation: Theory and Practice", which I taught as part of the PhD in Electrical Engineering, Department of Electrical Engineering of the Pontifícia Universidade Católica do Rio de Janeiro. Note: Although I am not currently giving this course I am updating the notebooks from time to time to meet software updates and remove bugs.

Flasked-Notebooks - Rendering IPython Notebooks using Flask

  •    Python

Dynamically executing and rendering notebooks that use Widgets for interactive pages.

nbtop - IPython Notebook server monitor inspired by htop

  •    Python

IPython Notebook server monitor inspired by htop. nbtop uses the kernel ids of running notebooks (queried from /api/sessions) and matches them to running processes on the server. If nbtop is pointed at a remote notebook server the memory and cpu percentage will be displayed as -99.

March-Madness-2017 - Kaggle Competition for Predicting NCAA Basketball Tourney Games

  •    Jupyter

Kaggle Competition for Predicting NCAA Basketball Tourney Games. Link to the associated blog post I wrote.

Pandas-Tutorial - Tutorial on Using Pandas

  •    Jupyter

I've been working with Pandas quite a bit lately, and figured I'd make a short summary of the most important and helpful functions in the library.

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