95 skills found · Page 1 of 4
yzhao062 / PyodA Python Library for Outlier and Anomaly Detection on Tabular, Text, and Image Data
vaexio / VaexOut-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
jazzband / TablibPython Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c.
camelot-dev / CamelotA Python library to extract tabular data from PDFs
mljar / Mljar SupervisedPython package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
astanin / Python TabulatePretty-print tabular data in Python, a library and a command-line utility. Repository migrated from bitbucket.org/astanin/python-tabulate.
h2oai / DatatableA Python package for manipulating 2-dimensional tabular data structures
frictionlessdata / Frictionless PyData management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
TabViewer / TabviewPython curses command line CSV and tabular data viewer
reubano / MezaA Python toolkit for processing tabular data
sktime / SkproA unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
OpenTabular / DeepTabDeepTab is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mambular, TabM, FT-Transformer, TabulaRNN, TabTransformer, and tabular ResNets.
ExtractTable / ExtractTable PyPython library to extract tabular data from images and scanned PDFs
frictionlessdata / Tabulator PyPython library for reading and writing tabular data via streams.
Alex-Lekov / AutoML AlexState-of-the art Automated Machine Learning python library for Tabular Data
piyushpathak03 / Recommendation SystemsRecommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems
denisenkom / PytdsPython DBAPI driver for MSSQL using pure Python TDS (Tabular Data Stream) protocol implementation
nirum / TableprintPretty console printing :clipboard: of tabular data in python :snake:
kxxoling / PTablePrettyTable is a simple Python library designed to make it quick and easy to represent tabular data in visually appealing ASCII tables.
keizerzilla / Telegram Chat ParserPython script to parse a Telegram chat history backup (JSON) into tabular format (CSV). No extra packages required, only Python 3.x!
