GitHub projects

Convolutional autoencoders for 3D image/field compression applied to reduced order Data Assimilation.

Biologically-Inspired and Machine Learning Algorithms in Python. [Deprecated]

Jupyter notebooks that cover how to implement from scratch different ML algorithms (ordinary least squares, gradient descent, k-means, alternating least squares), using Python NumPy, and how to then make these implementations scalable using Map/Reduce and Spark.

A minimal, educational, Pythonic implementation of autograd (~100 loc).

A slightly larger, somewhat feature-complete, PyTorch-inspired, NumPy implementation of a tensor reverse-mode automatic differentiation engine.

Ignite your models into blazing-fast machine learning APIs with a modern framework.

A little logger for machine learning research. Output any object to the terminal, CSV, TensorBoard, text logs on disk, and more with just one call to logger.log().

Debugging and visualization tool for machine learning and data science. It extensively leverages Jupyter Notebook to show real-time visualizations of data in running processes such as machine learning training.

A workflow engine for solving machine learning problems by combining in one analysis pipeline (i) feature engineering and machine learning (ii) model training and prediction (iii) table population and column evaluation via user-defined (Python) functions.

A framework for creating analytical web applications built on top of Plotly.js, React, and Flask

PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters

Lime is about explaining what machine learning classifiers (or models) are doing. It is able to explain any black box classifier, with two or more classes.

A dashboard library for interactive visualizations using flask socketio and react.

A visualization library for quick and easy generation of common plots in data analysis and machine learning.

A python package for data exploration and data analysis. [Deprecated]

implementation of the hdbscan algorithm in Python - used for clustering

Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters, has python API.

Self Organizing Map written in Python (Uses neural networks for data analysis).

Tools for exploratory data analysis in Python.

A data exploration platform designed to be visual, intuitive, and interactive.

Simple, realtime visualization of neural network training performance.

An API for plotting in Jupyter (IPython).

The power of Chart.js in Jupyter Notebook.

Pandas on PySpark (POPS).

An all-in-one NuPIC Hierarchical Temporal Memory visualization and debugging super-tool! [Deprecated]

A web-based visualization and debugging platform for NuPIC. [Deprecated]

GPU-based high-performance interactive OpenGL 2D/3D data visualization library.

A Python Framework for Wind Energy Analysis and Prediction.

The Python ensemble sampling toolkit for affine-invariant MCMC.

NumPy and Pandas interface to Big Data.

Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python.

[Deprecated]

A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy.

Rendering beautiful SVG maps in Python.

Unified interface to ggplot2 popular R packages.

Same API as ggplot2 for R. [Deprecated]

Simple plotting for Python. Wrapper for D3xterjs; easily render charts in-browser.

A plotting library for Python, based on D3.js.

A Python to Vega translator.

Interactive Web Plotting for Python.

Statistical modelling and econometrics in Python.

A Python library for symbolic mathematics.

A Pythonic algorithmic trading library.

Markov Chain Monte Carlo sampling toolkit.

Business Intelligence (BI) in Python (Pandas web interface) [Deprecated]

A high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. Documentation can be found here.

A tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.

A GitHub Repository Where you can Learn Datavisualizatoin Basics to Intermediate level.