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Name: Ayyappa Kuncham
Type: User
Bio: Data scientist and a software Developer with areas of interest in Machine Learning, Python-based Deep Learning
Location: New York City
Name: Ayyappa Kuncham
Type: User
Bio: Data scientist and a software Developer with areas of interest in Machine Learning, Python-based Deep Learning
Location: New York City
Building Natural Language Applications with TensorFlow, published by Packt
The library contains a number of interconnected Java packages that implement machine learning and artificial intelligence algorithms. These are artificial intelligence algorithms implemented for the kind of people that like to implement algorithms themselves.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)
Building Machine Learning Systems with Python by Packt Publishing
Building Recommender Systems with Machine Learning and AI, published by Packt
Convolutional Neural Network for Text Classification in Tensorflow
Code examples for “Interactive Data Visualization for the Web”
Cheat Sheets
Deep Learning Specialization by Andrew Ng on Coursera.
Repo for the Deep Reinforcement Learning Nanodegree program
An implementation of a deep learning recommendation model (DLRM)
Sales forecasting v3
Example code for running R on Hadoop
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Leetcode solution auto generator
Managed Machine Learning Systems and Internet of Things Live Lesson
An interactive book on deep learning. Much easy, so MXNet. Wow.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability.
Code from the r tutorial on my blog
My clone repository
My clone repository
Apache Spark
:orange_book: The probability and statistics cookbook
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, bitcoins and options).
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.