Ipython Libraries

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Ipython Libraries

Ready-to-run Docker images containing Jupyter applications

The container remains intact for restart after the Server exits.

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

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.

IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality. Additional PyRo tutorials: IPython Notebook(s) demonstrating scikit-learn functi…

Because sometimes you need to do it live

doitlive is a tool for live presentations in the terminal. It reads a file of shell commands and replays the commands in a fake terminal session as you type random characters. Requires Python >= 3…

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

The reference book for these and other Spark related topics is: The following notebooks can be examined individually, although there is a more or less linear 'story' when followed in sequence. By usi…

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.

This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this repository is to provide an example of a competitive analysis for those …

This repository contains all the data analytics projects that I've worked on in python.

This repository contains all the data analytics projects that I've worked on in python. Extract the ZIP and open it. Unfortunately I don't have any more specific instructions because how exactly this…

NoteBooks-Statistics-and-MachineLearning

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

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

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 to their own personal photos and videos.

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 f…

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.

It is an extension module of Python which is mostly written in "C". It provides various functions which are capable of performing the numeric computations with a high speed. NumPy provides various po…

:notebook: A growing collection of Jupyter Notebooks written in Python, OCaml and Julia for science examples, algorithms, visualizations etc

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…

[Book-2019] Pragmatic AI: An Introduction to Cloud-based Machine Learning

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…

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.

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…

Linux/WSL config to optimize ergonomics, security, and productivity: vim/neovim, zsh, tmux, i3, emacs, vscode, ipython, jupyter, ranger, fzf, kitty, xkb, selfquant, firejail, systemd, etc

This repo contains config files (commonly called dotfiles) targeting Linux andWSL. It is my humble attempt to optimize ergonomics, security, and productivity.No doubt that I spent too much time micro…

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