1473 Open source projects that are alternatives of or similar to Best Of Ml Python

A Streamlit application to play with machine learning models directly from the browser

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

This project will pull past game data from api-football, and use these statistics to predict the outcome of future premier league matches through machine learning.

Python package for Bayesian Machine Learning with scikit-learn API

Titanic assignment on Kaggle competition

Interactive network visualization in Python and Dash, powered by Cytoscape.js

Predicting Profitable Day Trading Positions using Decision Tree Classifiers. scikit-learn | Flask | SQLite3 | pandas | MLflow | Heroku | Streamlit

🦄 Scientific journal and sci-fi themed color palettes for ggplot2

Tool for visualizing and empirically analyzing information encoded in binary files

The Python-ARM Radar Toolkit. A data model driven interactive toolkit for working with weather radar data.

A jupyter notebook having all most frequent used code snippet for daily data scienceoperations

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Machine learning toolkits with Python

Leave One Feature Out Importance

Machine Learning Operator & Controller for Kubernetes

Run code interactively, inspect data, and plot. All the power of Jupyter kernels, inside your favorite text editor.

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

A WebGL viewer for UMAP or TSNE-clustered images

Predicting the winner of 2019 cricket world cup using random forest algorithm

D3 block magic for Jupyter notebook.

machine_learning_examples

Scrape any website, article or RSS/Atom Feed with ease!

A python package to assess cluster tendency

A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

NYC scikit-learn sprint (Sep 2018)

🎯 Personal data science and machine learning toolbox

A comprehensive dimensional reduction framework to recover the latent topology from high-dimensional data.

Turbodbc is a Python module to access relational databases via the Open Database Connectivity (ODBC) interface. The module complies with the Python Database API Specification 2.0.

Quora Kaggle Competition : Natural Language Processing using word2vec embeddings, scikit-learn and xgboost for training

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries

A Pandas Styler class for making beautiful tables

A gentle introduction to machine learning: data handling, linear regression, naive bayes, clustering

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.

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

A collection of data science and machine learning resources that I've found helpful (I only post what I've read!)

NYC WiMLDS scikit-learn open source sprint (Aug 24, 2019)

My Answer to 120 Data Science Interview Questions

Machine Learning for Spot Prices

This is the companion curriculum to my guide to becoming a data scientist.

📊 All of courses, assignments, exercises, mini-projects and books that I've done so far in the process of learning by myself Machine Learning and Data Science.

Python for Data Science (Seminar Course at UC Berkeley; AY 250)

A simplified framework and utilities for PyTorch

<Do it! 딥러닝 입문> 도서의 주피터 노트북

PyData, The Complete Works of

Client-side reusable Charting Library based on D3.js v5 that allows easy and intuitive use of charts and components that can be composed together creating amazing visualizations.

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

Predict materials properties using only the composition information!

Becoming better at data science every day

Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'

📈📊☕️☕️☕️An elegant modern declarative data visualization chart framework for Android. Extremely powerful, supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.极其精美而又强大的 Android 数据可视化图表框架,支持柱状图、条形图、折线图、曲线图、折线填充图、曲线填充图、气泡图、扇形图、环形图、散点图、雷达图、混合图等各种类型的多达几十种的信息图图表,完全满足工作所需.

d3-force graphs as React Components.

An interpreted relational query language that compiles to SQL.

A Flutter widget to use Apache ECharts (incubating) in a reactive way.

A JavaScript framework for interactive 3D and 2D visualizations

based on "Hands-On Machine Learning with Scikit-Learn & TensorFlow" (O'Reilly, Aurelien Geron)

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

Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python. Opensource analytics, predictive analytics over clickstream, sentiment analysis, AB tests, machine learning, and Monte Carlo Markov Chain simulations, extending Pandas, Networkx and sklearn.

A Swiss-Army Knife for Data I/O

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.