Stars
Fuzzy Logic SciKit (Toolkit for SciPy)
Loads and prepares screw driving data from various experiments
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
A simple preprocessing method for Machine Learning
Free course that takes you from zero to Reinforcement Learning PRO 🦸🏻🦸🏽
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
RanCoord is a Python package for random sampling of geographic coordinates
Conditional GAN for generating synthetic tabular data.
ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Graph Neural Networks with Keras and Tensorflow 2.
Implementation of MoNet (mixture model CNN) and GAT (Graph Attention Network) tested on MNIST and Cora datasets using Tensorflow 2.0.
A Python package for manipulating 2-dimensional tabular data structures
A curated list of community detection research papers with implementations.
Materials for blogs and conferences
Evaluate real and synthetic datasets against each other
Metrics to evaluate quality and efficacy of synthetic datasets.
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Keras documentation, hosted live at keras.io
Tutorials and training material for the H2O Machine Learning Platform
Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
PlaidML is a framework for making deep learning work everywhere.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Computational experiments for the paper "A Comparison of AutoML Tools for Machine Learning, Deep Learning and XGBoost" (IJCNN 2021)