6980 Open source projects that are alternatives of or similar to Docker Iocaml Datascience

Source code and data analyses for the Sci-Hub Coverage Study

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

Materials for GWU DNSC 6279 and DNSC 6290.

A collection of Jupyter Notebooks for learning Python for Data Science.

Create HTML profiling reports from pandas DataFrame objects

A Code-First Introduction to NLP course

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

The Go kernel for Jupyter notebooks and nteract.

Stock for Deep Learning and Machine Learning

Repository of code and resources related to different data science and machine learning topics. For learning, practice and teaching purposes.

Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.

Compilation of R and Python programming codes on the Data Professor YouTube channel.

An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

open source for wechat-official-account (ID: PyDataLab)

Jupyter notebooks from the scikit-learn video series

Extração de dados da API do CartolaFC, análise exploratória dos dados e modelos preditivos em R e Python - 2014-20. [EN] Data munging, analysis and modeling of CartolaFC - the most popular fantasy football game in Brazil and maybe in the world. Data cover years 2014-19.

An open-source, low-code machine learning library in Python

Probabilistic reasoning and statistical analysis in TensorFlow

Interactive reports to analyze machine learning models during validation or production monitoring.

experiments with python

Debugging, monitoring and visualization for Python Machine Learning and Data Science

This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.

A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci

Production Data Science: a workflow for collaborative data science aimed at production

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

Data Science Best Practices with pandas

A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book

H2O.ai Machine Learning Interpretability Resources

Tutorial: Web scraping in Python with Beautiful Soup

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

food image to recipe with deep convolutional neural networks.

Ways of doing Data Science Engineering and Machine Learning in R and Python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Curso de Introducción a Machine Learning con Python

This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS)

Python supercharged for the fastai library

Temporary home for fastai v2 while it's being developed

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

Automatic extraction of relevant features from time series:

📘 The interactive computing suite for you! ✨

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"

Python pour Statistique et Science des Données -- Syntaxe, Trafic de Données, Graphes, Programmation, Apprentissage

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018

Introduction to Data Science

Python tools for data analysis

Codes and dashboards for 4th place solution for Kaggle's Home Credit Default Risk competition

The AI Application Platform We All Need. Human AND Machine Intelligence. Based on experience building AI solutions at Panasonic: robotics predictive maintenance, cold-chain energy optimization, Gigafactory battery mfg, avionics, automotive cybersecurity, and more.

This is a tutorial for PyTorch Geometric on the YooChoose dataset

RadIO is a library for data science research of computed tomography imaging

¡Camino a una educación autodidacta en Ciencia de Datos!

Support content for my blog

Introduction to pandas Treehouse course

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

Association Rule Mining from Spatial Data for Crime Analysis