akirakaneshiro Goto Github PK
Name: Akira Kaneshiro
Type: User
Location: Las Vegas
Name: Akira Kaneshiro
Type: User
Location: Las Vegas
Source code for the "Practical Data Science in Python" tutorial
Machine learning workshop using Python, pandas, and scikit-learn. The first half of the day covered supervised classification using Logistic Regression and how to use cross validation to evaluate your models . The second half of the day covered unsupervised clustering with Kmeans as well as an overview of the data science process.
Files and notebooks from Alexis Perez for training in Python
Solutions in R/Python for the exercises in the book Doing Data Science by Rachel Schutt and Cathy O'Neil
Python Solutions to the Project Euler Problems
General Assembly Data Science 12
General Assembly Data Science DC
A repository for my work done in General Assembly's Python for Data Science Class.
Files for each hackhour topic... fork, beer, pizza
Example coding interview problems found through online resources, Cracking the Code book, mentors and colleagues. An additional robust resource for example interview questions and solutions is at https://github.com/mmihaljevic/algortihms_challenges.
Intro to Data Science at Columbia University
an introduction to Data Science using Python
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstartes basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.
Open Content for self-directed learning in data science
LeetCode题解,151道题完整版
Code for Columbia's COMS W4721 Machine Learning for Data Science
Python coded examples and documentation of machine learning algorithms.
Machine Learning for Data Science at Columbia DSI
boilerplate code, scripts, modules, data for Introduction to Machine Learning with Python
Code and data for Professor James Bagrow's, Math 295 (Data Science 2) at UVM, F14
Metis Data Science NY Bootcamp
All my solutions to the Metis coding challenges
The prework for Metis Data Science Bootcamp
UCB MIDS
MIT Data Science work in Python
Code accompanying the book "Machine Learning for Hackers"
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.