Ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.
Comet.ml allows machine learning teams to automatically track their machine learning code, experiments, hyperparameters and results. It works from every computer, whether it’s your laptop or a your favorite cloud provider.
Every day, interesting machine learning projects get posted to GitHub, but they soon disappear into the abyss if you're not quick to bookmark them. I've created a small collection of ML projects that stood out to me from HN, reddit, and GitHub. Preference was given to open source projects witht an online demo. Let me know if I missed any!
Michelangelo, is an internal ML-as-a-service platform that democratizes machine learning and makes scaling AI to meet the needs of business as easy as requesting a ride. Michelangelo enables internal teams to seamlessly build, deploy, and operate machine learning solutions at Uber’s scale.
The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables.
We believe this is best done together with the community and powered by automation.
We gathered 360 AI, ML, Blockchain conferences worldwide into a single list - the largest one you can find online. Enjoy 🙏
Fritz makes it easy to build these experiences with an end-to-end mobile ML platform. Get started at https://fritz.ai
Prodigy is a new annotation tool for creating training and evaluation data for machine learning models. It comes with an extensible, self-hosted back-end, active learning-powered models that update as you annotate, and a modern web application that helps you stay focused.
Nexosis provides a public API which allows developers to quickly add machine learning to applications.
ModelDepot is aiming to make advancements in machine learning more accessible to engineers.
Effortlessly find and use curated pre-trained models to build better products that are augmented by cutting edge strides in the field.
IBM Watson now integrates directly into Apple's ML Core, so developers can build AI-powered apps to help improve every part of your life. 🤖
Count is a machine learning company looking to quantify the organic data inside photos, video, and sound. Anybody that has lived in Manhattan understands the dynamics of the Shake Shack line in Madison Square Park. We thought it would be fun to practice our craft quantifying the Shake Shack line in real-time as our first experiment.
Sagify is a command-line utility to train and deploy Machine Learning and Deep Learning models on AWS SageMaker in a few simple steps!
Introducing a new way to interact with machine learning. Our brand new interactive dashboard makes our three step approach to ML even simpler. Just upload your data, build a model, and retrieve your results.
Mate Labs is trying to enable Machine Learning and Deep Learning to one and all. Irrespective of whether a user knows how to code or not.
Gradient allows you to create, train, and use machine learning models with the full power of TensorFlow API on .NET
- Train and run models on any hardware platform
- Use distributed training features
- Track your progress with Tensorboard
- Use C#