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Course - 5; Specialization: Applied Data Science with Python; University Of Michigan
University of Washington
Repository for CS 506 / ENG 500 as taught by Mark Crovella - BU Computer Science
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Introduction to Deep Neural Networks with Keras and Tensorflow
Slides from MXNet Gluon tutorials
通过 MXNet / Gluon 来动手学习深度学习
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Introduction to Neural Networks with Keras, O'Reilly Artificial Intelligence Conference 2017, Tutorial
Material for learning data science through illustrated examples and problem sets.
An interactive book on deep learning. Much easy, so MXNet. Wow.
CIFAR-10 dataset with 60,000 images is used to compare the two different CNN models with different number of layers, different parameters and hyperparameters like epochs , batch size ,etc... and finally the different validation accuracies and loss is obtained .One model is more complex than the other and produces better results than the former .
Recipes for using Python's pandas library
(great)Material for the pandas tutorial at EuroScipy 2016
Jupyter notebook and datasets from the pandas Q&A video series
Practice your pandas skills!
Pandas tutorial for SciPy2015 and SciPy2016 conference
Code, Notebooks and Examples from Practical Business Python
PyCon 2015 Pandas tutorial materials
Jupyter notebooks from the scikit-learn video series
Introduction to Scikit-Learn and Pandas
DIPA course titled Practical Machine Learning on Graphs
StellarGraph - Machine Learning on Graphs
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
TensorFlow Tutorial and Examples for beginners
How to use TensorLayer
A variation on the classic game Tic-Tac-Toe.
Twitter Sentiment Analysis with Gensim Word2Vec and Keras Convolutional Network
word2vec workshop - a conceptual introduction and practical application
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.