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Name: Pranav
Type: User
Name: Pranav
Type: User
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
A collection of notebook to learn the Applied Predictive Modeling using Python.
Data and code from Applied Predictive Modeling (2013)
apricot implements submodular selection for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Documentation and samples for ArcGIS API for Python
Pythonic Bayesian Belief Network Package, supporting creation of and exact inference on Bayesian Belief Networks specified as pure python functions.
CLEVR graph: A dataset for graph based reasoning
Comp 576
🌀 Stanford CS 228 - Probabilistic Graphical Models
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
Interface between a DBN model and CNN models to learn from demonstrations
Simple Tensorflow implementation of Densenet using Cifar10, MNIST
Python package built to ease deep learning on graph, on top of existing DL frameworks.
10 differentiable physical simulators built with Taichi differentiable programming (DiffTaichi, ICLR 2020)
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
The fastai book, published as Jupyter Notebooks
This code converts GeoJSON to shape files.
Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!
Build Graph Nets in Tensorflow
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Jekyll-based static site for The Programming Historian
John Hunter Excellence in Plotting Contest
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Reference implementations of popular deep learning models.
Lime: Explaining the predictions of any machine learning classifier
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.