a-agmon

a-agmon's Stars

• aksnzhy/xlearn

  High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

  Language:C++3.1k519

• yonigottesman/spark_fm

  spark factorization machine on movielens

  Language:Scala2

• yonigottesman/recommendation_playground

  Language:Jupyter Notebook64

• eugeneyan/recsys-nlp-graph

  🛒 Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.

  Language:Python13729

• bab2min/tomotopy

  Python package of Tomoto, the Topic Modeling Tool

  Language:C++56363

• maciejkula/triplet_recommendations_keras

  An example of doing MovieLens recommendations using triplet loss in Keras

  Language:Jupyter Notebook421103

• ankoorb/Side-Projects

  Language:Jupyter Notebook51

• awjuliani/DeepRL-Agents

  A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

  Language:Jupyter Notebook2.2k826

• david-cortes/contextualbandits

  Python implementations of contextual bandits algorithms

  Language:Python753148

• LaunchpadAI/space-bandits

  Language:Jupyter Notebook10230

• rymc/n2d

  A deep clustering algorithm. Code to reproduce results for our paper N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding.

  Language:Python12921

• zhoushengisnoob/DeepClustering

  Methods and Implements of Deep Clustering

  2.9k415

• yzzhang/machine-learning

  Language:Jupyter Notebook5353

• Tony607/Keras_Deep_Clustering

  How to do Unsupervised Clustering with Keras

  Language:Jupyter Notebook238138

• MengtingWan/goodreads

  code samples for the goodreads datasets

  Language:Jupyter Notebook25159

• GunhoChoi/PyTorch-FastCampus

  PyTorch로 시작하는 딥러닝 입문 CAMP (2017.7~2017.12) 강의자료

  Language:Jupyter Notebook472230

• maciejkula/spotlight

  Deep recommender models using PyTorch.

  Language:Python3k428

• HarshdeepGupta/recommender_pytorch

  A recommender system in PyTorch from scratch.

  Language:Python11633

• kapadias/medium-articles

  Language:HTML211290

• WillKoehrsen/wikipedia-data-science

  Working with and analyzing Wikipedia Data

  Language:Jupyter Notebook692288

• PGuti/DeepBeer

  Experimentations on beers recsys using Keras

  Language:Jupyter Notebook2516

• nanxstats/deep-learning-recipes

  🍱 R implementation for selected machine learning methods with deep learning frameworks (Keras, Tensorflow)

  Language:R4610

• lyst/lightfm

  A Python implementation of LightFM, a hybrid recommendation algorithm.

  Language:Python4.8k693

• benfred/implicit

  Fast Python Collaborative Filtering for Implicit Feedback Datasets

  Language:Python3.6k612

• aws-samples/aws-machine-learning-university-accelerated-nlp

  Machine Learning University: Accelerated Natural Language Processing Class

  Language:Jupyter Notebook2.4k611

• fastai/course-nlp

  A Code-First Introduction to NLP course

  Language:Jupyter Notebook3.4k1.5k

• MGensheimer/nnet-survival

  Discrete-Time Survival Model for Neural Networks

  Language:Python8928

• sebp/scikit-survival

  Survival analysis built on top of scikit-learn

  Language:Python1.1k216

• phuijse/bagging_pu

  Simple sklearn based python implementation of Positive-Unlabeled (PU) classification using bagging based ensembles

  Language:Jupyter Notebook9019

• aldro61/pu-learning

  Positive and unlabeled learning wrappers for scikit-learn

  Language:Python23386