6774 Open source projects that are alternatives of or similar to Python Machine Learning Book 2nd Edition

brief introduction to Python for 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.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

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.

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Exercises for hierarchical clustering with Python 3 and scipy as Jupyter Notebooks

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

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

A library for debugging/inspecting machine learning classifiers and explaining their predictions

General Assembly's 2015 Data Science course in Washington, DC

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

Association Rule Mining from Spatial Data for Crime Analysis

A collection of notebooks of my Machine Learning class written in python 3

The "Python Machine Learning (1st edition)" book code repository and info resource

🤖⚡️ scikit-learn tips

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

🎓 Jupyter notebooks from UFC data science course

Dive into Machine Learning with Python Jupyter notebook and scikit-learn! First posted in 2016, maintained as of 2021. Pull requests welcome.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

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

Data Science Best Practices with pandas

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

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

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

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

[UNMAINTAINED] Automated machine learning- just give it a data file! Check out the production-ready version of this project at ClimbsRocks/auto_ml

A simple probabilistic programming language.

Python package for Bayesian Machine Learning with scikit-learn API

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

¡Camino a una educación autodidacta en Ciencia de Datos!

Curso de Introducción a Machine Learning con Python

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H2O.ai Machine Learning Interpretability Resources

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

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Quiz & Assignment of Coursera

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

Efficient Learning of Augmentation Policy Schedules

Framework for setting up predictive analytics services

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

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

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

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

An intro to Python & programming for wanna-be data scientists

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

A unified framework for machine learning with time series

food image to recipe with deep convolutional neural networks.

The 3rd edition of course.fast.ai

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

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

The Hitchhiker's Guide to Data Science for Social Good

This is a collection of all the code that can be found on my YouTube channel Sigma Coding.