AmazaspShumik

AmazaspShumik's Stars

• phillipi/pix2pix

  Image-to-image translation with conditional adversarial nets

  Language:Lua10.2k3222101.7k

• vahidk/EffectiveTensorflow

  TensorFlow tutorials and best practices.

  8.6k34418906

• catboost/catboost

  A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

  Language:Python8.2k1912.4k1.2k

• bayesian-optimization/BayesianOptimization

  A Python implementation of global optimization with gaussian processes.

  Language:Python8k1303661.6k

• wiseodd/generative-models

  Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

  Language:Python7.4k297662k

• hunkim/DeepLearningZeroToAll

  TensorFlow Basic Tutorial Labs

  Language:Jupyter Notebook4.5k422752.7k

• BinRoot/TensorFlow-Book

  Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

  Language:Jupyter Notebook4.5k297281.2k

• tdeboissiere/DeepLearningImplementations

  Implementation of recent Deep Learning papers

  Language:Python1.8k13274649

• keplr-io/quiver

  Interactive convnet features visualization for Keras

  Language:JavaScript1.8k5661223

• Yelp/MOE

  A global, black box optimization engine for real world metric optimization.

  Language:C++1.3k61309139

• adeshpande3/Tensorflow-Programs-and-Tutorials

  Implementations of CNNs, RNNs, GANs, etc

  Language:Jupyter Notebook1.1k605322

• geek-ai/irgan

  IRGAN SIGIR paper experimental code

  Language:Python6224937242

• soroushmehr/sampleRNN_ICLR2017

  SampleRNN: An Unconditional End-to-End Neural Audio Generation Model

  Language:Python5382726141

• robi56/awesome-bayesian-deep-learning

  A curated list of resources dedicated to bayesian deep learning

  41337085

• axelbrando/Mixture-Density-Networks-for-distribution-and-uncertainty-estimation

  A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)

  Language:Jupyter Notebook340231190

• YerevaNN/Dynamic-memory-networks-in-Theano

  Implementation of Dynamic memory networks by Kumar et al. http://arxiv.org/abs/1506.07285

  Language:Python331387109

• aicodes/tf-bestpractice

  Tensorflow Best Practices

  33024439

• amueller/scipy-2017-sklearn

  Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller

  Language:Jupyter Notebook2851510225

• oduerr/dl_tutorial

  Tutorials for deep learning

  Language:Jupyter Notebook25329493

• autoliuweijie/DeepLearning

  Some practices about deep learning

  Language:Jupyter Notebook22691222

• andreweskeclarke/learning-rank-public

  Learning Rank

  Language:Python797226

• amueller/quick-ml-intro

  One hour interactive training for ML with scikit-learn

  Language:Jupyter Notebook7413020

• dariasor/TreeExtra

  Additive Groves, Bagged Trees with Feature Evaluation, Interaction Detection, Visualization of Feature Effects.

  Language:C++669520

• AmazaspShumik/Mixture-Models

  Hierarchical Mixture of Experts,Mixture Density Neural Network

  Language:Jupyter Notebook4531217

• YerevaNN/Deep-Learning-Papers-Reading-Roadmap

  Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

  34809

• AmazaspShumik/MapReduce-Machine-Learning

  Map-Reduce implementation of some machine learning algorithms

  Language:Python222413

• opentable/mercury

  Mercury is a bot for handling in-code static translations.

  Language:JavaScript202107

• atechnicolorskye/Bayesian-Models-Machine-Learning-EECS6720

  Language:Jupyter Notebook11309

• AmazaspShumik/JDSAL

  Data Structures & Algorithms in Java. Preparing for interview

  Language:Java2200

• JulienSiems/IRDM-2017-Option-2

  Code for IRDM Project Option 2 at UCL

  Language:Python1400