rameshjay Goto Github PK
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Examples from the book A Tour of C++
my bash.d directory
Programming examples of Joseph K. Blitzstein: Introduction to Probability, written in Python.
Introduction to Scientific Python
Code for a workshop on statistical interference using computational methods in Python.
IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018
Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]
Credit-Risk Modelling Libraries
Teaching materials for the probabilistic graphical models and deep learning classes at Stanford
Code examples for “Interactive Data Visualization for the Web”
code for Data Science From Scratch book
Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017
Solutions to the exercises of the Discovering Modern C++: An Intensive Course for Scientists, Engineers and Programmers book by Peter Gottschling.
Source code for my collection of articles on using pandas.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Notes and code for John V. Guttag's "Introduction to Computation and Programming Using Python"
Notebooks and code for the book "Introduction to Machine Learning with Python"
Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability
A collection of IPython notebooks covering various topics.
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
This repository contains the code examples for the book Pro Python Best Practices: Debugging, Testing and Maintenance published by Apress in 2017.
The official online compendium for Mining the Social Web, 3rd Edition (O'Reilly, 2018)
IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)
Text and supporting code for Modeling and Simulation in Python
Parallel computing in Python tutorial materials
Probability 140
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Companion code repository for the O'Reilly "Python and R for the Modern Data Scientist" book.
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.