7036 Open source projects that are alternatives of or similar to Industry Machine Learning

Virgilio is developed and maintained by these awesome people. You can email us virgilio.datascience (at) gmail.com or join the Discord chat.

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The blog post about Kubeflow, including all materials

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Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications

👨🏽‍🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋

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

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A collection of demos showcasing automated feature engineering and machine learning in diverse use cases

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Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js

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food image to recipe with deep convolutional neural networks.

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

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

📚 [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记

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

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This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

DeltaPy - Tabular Data Augmentation (by @firmai)

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

experiments with python

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

Collection of useful data science topics along with code and articles

useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html

阿水的数据竞赛开源分支

H2O.ai Machine Learning Interpretability Resources

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¡Camino a una educación autodidacta en Ciencia de Datos!

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

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🚀 Build and manage real-life data science projects with ease!

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

Code for Machine Learning for Algorithmic Trading, 2nd edition.

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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 ;)

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

Code, exercises and tutorials of my personal blog ! 📝

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H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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All course materials for the Zero to Mastery Machine Learning and Data Science course.

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)