Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Upscale an image by a factor of 4, while generating photo-realistic details.
Collection of models for Core ML
A list of popular deep learning models related to classification, segmentation and detection problems
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
Localize and identify multiple objects in a single image.
Launch machine learning models into production using flask, docker etc.
Machine learning Guide. Learn all about Machine Learning Tools, Libraries, Frameworks, and Training Models.
State-of-the art Automated Machine Learning python library for Tabular Data
Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
A CoreML model which classifies images of food
Identify sounds in short audio clips
Detect humans in an image and estimate the pose for each person
Predict hourly weather features given historical data for a specific location
Detect the sentiment captured in short pieces of text
Keras implementation of sketch inversion using deep convolution neural networks (synthesising photo-realistic images from pencil sketches)
Deep active inference agents using Monte-Carlo methods