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Learn Python Through Data Processing in Pandas
Applied Machine Learning with Python
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
Exercises for the book Applied Predictive Modeling by Kuhn and Johnson (2013)
A collection of notebook to learn the Applied Predictive Modeling using Python.
:exclamation: This is a read-only mirror of the CRAN R package repository. AppliedPredictiveModeling — Functions and Data Sets for 'Applied Predictive Modeling'. Homepage: http://appliedpredictivemodeling.com/
Data and code from Applied Predictive Modeling (2013)
Approaching (Almost) Any Machine Learning Problem
Machine Learning University: Accelerated Tabular Data Class
Machine Learning University: Decision Trees and Ensemble Methods
notebooks that are used at calmcode.io
caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models
Official content for Harvard CS109
Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Course materials
All notes and materials for the CS229: Machine Learning course by Stanford University
Exercises and solutions to Stanford CS229 Machine Learning in Python
🍟 Stanford CS229: Machine Learning
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
A roadmap for those looking to start or expand a career in the data community
Compiled Notes for all 9 courses in the Coursera Data Science Specialization
A collection of datasets of ML problem solving
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Code from the book "Deep Learning with R, 2nd Edition"
Example implementations of common machine learning projects in chemistry.
A list of all public EEG-datasets
This repository has exercises for videos taught on the YouTube channel 'learndataa'.
Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.