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Coursera's Data Science Specialization
http://DataScienceSpecialization.github.io
Hands-on tutorial on deep learning with a special focus on Natural Language Processing (NLP)
Deep Learning Tutorial notes and code. See the wiki for more info.
Homework/Classwork for my DSE 200 Python for Data Analysis Class at UC San Diego (UCSD)
Repo for my graduate data science machine learning class at UCSD (UC San Diego). This course provides a broad introduction to the practical side of machine-learning and data analysis. The topics covered in this class include topics in supervised learning, such as k-nearest neighbor classifiers, decision trees, boosting and perceptrons, and topics in unsupervised learning, such as k-means, PCA and Gaussian mixture models.
Files used in tutorials
Article on Ensemble Models
Introduction to Deep Learning for Natural Language Processing
Fortran and Python examples to accompany the book "Computer Simulation of Liquids" by Michael P. Allen and Dominic J. Tildesley (2nd edition, Oxford University Press, 2017). Use the "Clone or download" button, or follow the "...releases" link below.
Python pipeline (forked to ChangLab).
A set of tools for simulation of fractional Brownian motion
Python tools for geographic data
GeoRasters is a Python module that provides a fast and flexible tool to work with GIS raster files.
Series of GeoSpatial/GIS Python code examples (Python GIS CookBook)
IPython notebook for crime GIS data mining.
GIS Python Codes
Python module provides a fast and flexibletool to work with GIS raster files.
some functions for working with the Python GIS toolchain (fiona, shapely, pyproj, etc.)
An IPython notebook showing the basics of implementing gradient descent and stochastic gradient descent in Python
Introduction to Machine Learning using Python
Introduction to Deep Learning
Introduction to Statistics using Python
GitHub Repository to accompany my YouTube series of videos on Introductory Data Science using R.
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
A collection of IPython notebooks covering various topics.
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013) : Python code
A collection of Kaggle solutions. Not very polished.
DAT21 Linear Regression Assignment
Codes for Kaggle Competitions
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.