Role2vecA scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).
Stars: ✭ 134 (+83.56%)
NMFADMMA sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).
Stars: ✭ 39 (-46.58%)
gan tensorflowAutomatic feature engineering using Generative Adversarial Networks using TensorFlow.
Stars: ✭ 48 (-34.25%)
TsfreshAutomatic extraction of relevant features from time series:
Stars: ✭ 6,077 (+8224.66%)
DeltapyDeltaPy - Tabular Data Augmentation (by @firmai)
Stars: ✭ 344 (+371.23%)
NniAn open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Stars: ✭ 10,698 (+14554.79%)
GensimTopic Modelling for Humans
Stars: ✭ 12,763 (+17383.56%)
CodesearchnetDatasets, tools, and benchmarks for representation learning of code.
Stars: ✭ 1,378 (+1787.67%)
Amazing Feature EngineeringFeature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
Stars: ✭ 218 (+198.63%)
TadwAn implementation of "Network Representation Learning with Rich Text Information" (IJCAI '15).
Stars: ✭ 43 (-41.1%)
BagofconceptsPython implementation of bag-of-concepts
Stars: ✭ 18 (-75.34%)
Feature SelectionFeatures selector based on the self selected-algorithm, loss function and validation method
Stars: ✭ 534 (+631.51%)
DanmfA sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
Stars: ✭ 161 (+120.55%)
Awesome Feature EngineeringA curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
Stars: ✭ 433 (+493.15%)
Textfeatures👷♂️ A simple package for extracting useful features from character objects 👷♀️
Stars: ✭ 148 (+102.74%)
Color recognition🎨 Color recognition & classification & detection on webcam stream / on video / on single image using K-Nearest Neighbors (KNN) is trained with color histogram features by OpenCV.
Stars: ✭ 154 (+110.96%)
Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
Stars: ✭ 86 (+17.81%)
BlurrData transformations for the ML era
Stars: ✭ 96 (+31.51%)
TsfelAn intuitive library to extract features from time series
Stars: ✭ 202 (+176.71%)
autoencoders tensorflowAutomatic feature engineering using deep learning and Bayesian inference using TensorFlow.
Stars: ✭ 66 (-9.59%)
Php MlPHP-ML - Machine Learning library for PHP
Stars: ✭ 7,900 (+10721.92%)
ChiveJapanese word embedding with Sudachi and NWJC 🌿
Stars: ✭ 63 (-13.7%)
EvalneSource code for EvalNE, a Python library for evaluating Network Embedding methods.
Stars: ✭ 67 (-8.22%)
MetriculousMeasure and visualize machine learning model performance without the usual boilerplate.
Stars: ✭ 71 (-2.74%)
Linkedingiveaway👨🏽🏫You can learn about anything over here. What Giveaways I do and why it's important in today's modern world. Are you interested in Giveaway's?🔋
Stars: ✭ 67 (-8.22%)
Ntds 2017Material for the EPFL master course "A Network Tour of Data Science", edition 2017.
Stars: ✭ 61 (-16.44%)
Ai PlatformAn open-source platform for automating tasks using machine learning models
Stars: ✭ 61 (-16.44%)
GraphiaA visualisation tool for the creation and analysis of graphs
Stars: ✭ 67 (-8.22%)
Collaborative Deep Learning For Recommender SystemsThe hybrid model combining stacked denoising autoencoder with matrix factorization is applied, to predict the customer purchase behavior in the future month according to the purchase history and user information in the Santander dataset.
Stars: ✭ 60 (-17.81%)
BudgetmlDeploy a ML inference service on a budget in less than 10 lines of code.
Stars: ✭ 1,179 (+1515.07%)
SeabornStatistical data visualization in Python
Stars: ✭ 9,007 (+12238.36%)
Storytelling With DataCourse materials for Dartmouth Course: Storytelling with Data (PSYC 81.09).
Stars: ✭ 59 (-19.18%)
DogtorchWho Let The Dogs Out? Modeling Dog Behavior From Visual Data https://arxiv.org/pdf/1803.10827.pdf
Stars: ✭ 66 (-9.59%)
VerticapyVerticaPy is a Python library that exposes sci-kit like functionality to conduct data science projects on data stored in Vertica, thus taking advantage Vertica’s speed and built-in analytics and machine learning capabilities.
Stars: ✭ 59 (-19.18%)
DatacomparerdataCompareR is an R package that allows users to compare two datasets and view a report on the similarities and differences.
Stars: ✭ 58 (-20.55%)
Datacamp🍧 A repository that contains courses I have taken on DataCamp
Stars: ✭ 69 (-5.48%)
RsparklingRSparkling: Use H2O Sparkling Water from R (Spark + R + Machine Learning)
Stars: ✭ 65 (-10.96%)
OpenrefineOpenRefine is a free, open source power tool for working with messy data and improving it
Stars: ✭ 8,531 (+11586.3%)
Rumble⛈️ Rumble 1.11.0 "Banyan Tree"🌳 for Apache Spark | Run queries on your large-scale, messy JSON-like data (JSON, text, CSV, Parquet, ROOT, AVRO, SVM...) | No install required (just a jar to download) | Declarative Machine Learning and more
Stars: ✭ 58 (-20.55%)
Dna GanDNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
Stars: ✭ 65 (-10.96%)
Drake ExamplesExample workflows for the drake R package
Stars: ✭ 57 (-21.92%)
TeneA sparsity aware implementation of "Enhanced Network Embedding with Text Information" (ICPR 2018).
Stars: ✭ 69 (-5.48%)
W2vWord2Vec models with Twitter data using Spark. Blog:
Stars: ✭ 64 (-12.33%)
Usss iccv19Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
Stars: ✭ 57 (-21.92%)
Etherscan MlPython Data Science and Machine Learning Library for the Ethereum and ERC-20 Blockchain
Stars: ✭ 55 (-24.66%)
ChicksexerA Python package for gender classification.
Stars: ✭ 64 (-12.33%)
Ds and ml projectsData Science & Machine Learning projects and tutorials in python from beginner to advanced level.
Stars: ✭ 56 (-23.29%)
LifetimesLifetime value in Python
Stars: ✭ 1,082 (+1382.19%)