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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! 😀)
Automatically exported from code.google.com/p/ase-atomistic-potential-tests
Implementation of predictive maintenance for Azure Machine Learning in Python.
Biosignal Processing in Python
Code snippets from Jason Brownlee's ML and Deep Learning books.
ML tutorials from Citrine (http://www.citrine.io/blog/?offset=1434641580000)
Shared code for data transforms, calling your model or just having fun with deep learning
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
Complete machine learning model codes
common data analysis and machine learning tasks using python
a curated list of R tutorials for Data Science, NLP and Machine Learning
Understanding and Predicting Property Maintenance Fines
Nice and clean Online Shop app UI by using #Flutter.
This is for idea
This is an eCommerce minimalist template with a clean and beautiful design for Flutter.
Presentations from H2O meetups & conferences by the H2O.ai team
Tutorials and training material for the H2O Machine Learning Platform
Slides and code examples for H2O tutorials at various events
This project is to build a model that guesses the human activities like Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing or Laying.
Notebooks and code for the book "Introduction to Machine Learning with Python"
A collection of IPython notebooks covering various topics.
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
Some work on Kaggle data for fun
This notebook uses data from Kaggle competition "Titanic: Machine Learning from Disaster". Firstly, I engineer features to get maximum from the limited data available, and fill missing values of Age variable using linear regression. Then I compare performance of multiple classifiers, such as: logistic regression, SVM, k - nearest neighbours, Naive Bayes, Decision Tree Classifier. I also use ensemble methods such as random forest, bagging, boosting and voting classifier. I use grid search and cross validation to tune up the parameters of classifiers.
Public/backup repository of the LAMMPS MD software package
LAMMPS Membrane Builder for n-phase biomembrane systems
Open Content for self-directed learning in data science
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.