Jupyter-notebook Libraries

A live audio spectrum analyzer using pyAudio, matplotlib and scipy. A series of Jupyter notebooks and python files which stream audio from a microphone using pyaudio.

IPyPlot offers 3 main functions which can be used for displaying images in notebooks: and use any of the available plotting functions shown below (notice execution times).

This repository contains an SDK and example Jupyter notebooks to showcase its use. Interpret-Text incorporates community developed interpretability techniques for NLP models and a visualization dashb…

A Python 3 library for programmatically generating SVG images (vector drawings) and rendering them or displaying them in a Jupyter notebook. drawSvg is available on PyPI:

This is a utility that uses supervised machine learning to detect phishing domains from the Certificate Transparency log network. The firehose of domain names and SSL certificates are made available …

Notebooks as published on unsupervised-learning.com (RIP).

Self-hosted, 100% free to use and fully open source. Supports a wide range of product analytics use cases. We're currently working on extending the range of marketing related use cases. Objectiv curr…

The book demonstrates how Python can be used to study cultural materials such as song lyrics, short stories, newspaper articles, tweets, Reddit posts, and film screenplays. It also introduces computa…

My jupyter notebooks/code samples from Chris Albon's Machine Learning with Python Cookbook

The recommended way to fully experience the book is by running the Jupyter notebooks: You can test your installation by running

There are two options. Note: On each of those options, you'll find: No installations needed. Note: On each notebook, click on "Open in Colab", in order to open it on Google Colab Worried about whethe…

In this repository I collect my adventures in the Cryptography world. What to expect? Directories are organized by categories (S = Symmetric, P = Public, E = Extra) Each directory will have a README.…

You may consume them in different ways:

There are two options. Note: On each of those options, you'll find: No installations needed. Note: On each notebook, click on "Open in Colab", in order to open it on Google Colab

This repository contains the problem sets for Stanford CS229 (Machine Learning) on Coursera translated to Python 3. It also contains some of my notes. The following Python packages are used: You can …

The following is the textbook used for the Scientific Computing Chemists course intended to teach chemists and chemistry students basic computer programming in Python and Jupyter Notebooks and advanc…

Notebooks come alive when interactive widgets are used. Users can visualize and control changes in the data and the model. Learning becomes an immersive, plus fun, experience. However, learning and e…

I am working on command line argument version where you will be able to download selected stocks with this snippet too. This script can run on multiple Operating Systems. Follow the instructions ment…

My collection of geophysical notes written as Jupyter notebooks. (Mostly obsolete now, don't have time for a proper update; for example I stopped wasting my time with jupyter widgets and Panel for in…

Being specialized in domains like computer vision and natural language processing is no longer a luxury but a necessity which is expected of any data scientist in today’s fast-paced world! With a han…

You can also launch an interactive environment to play with the code by yourself, using one of these platforms: And more will come... soon! 🚅 You can also launch an interactive environment to play wi…

This is a Web Application designed to train Machine Learning pipelines using MLJAR AutoML, specifically tailored for tabular data. All the generated models are compressed into an archive format, allo…

This books was written in partnership with Pragmatic AI Labs. You can continue learning about these topics by: Building Cloud Computing Solutions at Scale Specialization Launch Your Career in Cloud C…

Key Python Packages:

To overcome the filesize limit of 100mb on GitHub, the dataset is split by year as: We recommend using Pandas to load the dataset. Example to load a single year: Or to load everything as one big Data…

The overall objective of this toolkit is to provide and offer a free collection of data analysis and machine learning that is specifically suited for doing data science. Its purpose is to get you sta…

Analyzing the IRIS dataset with Sci-Pype This notebook shows how to make new predictions with cached IRIS Classifier Models + Analysis housed in redis. This notebook shows how to make new predictions…