Artificial Intelligence Deep Learning Machine Learning Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
🍊 📊 💡 Orange: Interactive data analysis
Porn images detector with python, tensorflow, scikit-learn and opencv.
A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
a delightful machine learning tool that allows you to train, test, and use models without writing code
Machine Learning and NLP: Text Classification using python, scikit-learn and NLTK
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
Amazing Feature Engineering
Feature 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.
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Hummingbird compiles trained ML models into tensor computation for faster inference.
Convert scikit-learn models and pipelines to ONNX
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Library for Semi-Automated Data Science
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.
An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.
Bet On Sibyl
Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)
Fast and memory-efficient clustering
Virgilio is developed and maintained by these awesome people.
You can email us virgilio.datascience (at) gmail.com or join the Discord chat.
A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.
Scikit-learn compatible estimation of general graphical models
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
An intuitive library to add plotting functionality to scikit-learn objects.
Stacked Generalization (Ensemble Learning)
pymc-learn: Practical probabilistic machine learning in Python
Machine Learning inference engine for Microcontrollers and Embedded devices
🛠 All-in-one web-based IDE specialized for machine learning and data science.
A library for machine learning research on motion capture data
Interactive SVM Explorer, using Dash and scikit-learn
An implementation of Caruana et al's Ensemble Selection algorithm in Python, based on scikit-learn
Practical Machine Learning With Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Qlik Py Tools
Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
Machine Learning for High Energy Physics.