Weights & Biases

A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.

Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.

Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

It lets you run or deploy machine learning models, massively parallel compute jobs, task queues, web apps, and much more, without your own infrastructure.

BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.

Firebase Predictions uses the power of Google’s machine learning to create dynamic user groups based on users’ predicted behavior.

Machine learners share, stress test, and stay up-to-date on all the latest ML techniques and technologies. Discover a huge repository of community-published models, data & code for your next project.

Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem.

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

It is a Recommender as a Service with easy integration and powerful Admin UI. The Recombee recommendation engine can be applied to any domain that has a catalog of items and is interacted by a large number of users. Applicable to web and mobile apps, It improves user experience by showing the most relevant content for individual users.

It provides all you need to build and deploy computer vision models, from data annotation and organization tools to scalable deployment solutions that work across devices.

Lamina helps you integrate Deep Learning models like Sentiment Analysis and Entity Extraction into your products with a simple API call. Relieving you of getting data, creating a model and training them which would be compute-intensive.

Gradient° is a suite of tools for exploring data and training neural networks. Gradient° includes 1-click Jupyter notebooks, a powerful job runner, and a python module to run any code on a fully managed GPU cluster in the cloud. Gradient is also rolling out full support for Google's new TPUv2 accelerator to power even more newer workflows.

It is a high-performance cloud computing and ML development platform for building, training and deploying machine learning models. Tens of thousands of individuals, startups and enterprises use it to iterate faster and collaborate on intelligent, real-time prediction engines.

Delight your users with personalised content recommendations. It's easy to set up and works with or without collaborative data. The Lateral API is trained on 10s of millions of high quality documents from law, academia and journalism. It can understand any document and provide intelligent recommendations.

Dasha is a conversational AI as a Service platform. Dasha lets you create conversational apps that are more human-like than ever before, quicker than ever before and quickly integrate them into your products.

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

Wise.io builds machine intelligence products that make it easy for companies to derive actionable insight from their greatest corporate resource: their data.

It accelerates ML development. It provides an instant infrastructure for your ML projects. You can think of it as the Heroku of MLOps or the AWS lambda functions for ML, all powered by GPUs.

It is a development environment and hosting solution for machine learning models. No servers to manage, no configuration, no headaches. It just works. It is the fastest way to add production-ready ML into an app.

It is a machine learning profiler. It helps data scientists and ML engineers make model training and inference faster and more efficient.

It is a platform that makes it really easy to build, track and deploy models. It is deployed on a cluster on your own cloud so that the data never leaves your environment and you don't incur any data egress costs.

It is a fully-managed, cloud native feature platform that operates and manages the pipelines that transform raw data into features across the full lifecycle of an ML application.

It is a robust & flexible API to build unique product recommendations into any digital ecommerce experience. Developers can use a simple and flexible API to build machine learning powered recommendations on your company’s digital storefronts using as few as 6 lines of code, driving better conversions and increasing average order value. It comes with advanced flexibility so you can completely customize the recommendations displayed on your online stores.

It provides a way to deploy robust, repeatable machine learning pipelines along with monitoring, auditing, version tracking, and reproducibility, and delivers an enterprise-ready, easy to install, secure execution environment for your ML workflows.

It has a unified, easy-to-use API and platform to access and deploy GPU workloads to any provider. It guarantees inference and training jobs will run on time at optimal cost.

It is an evaluation tool that fits into your development and production pipelines to help you ship high-quality models with confidence. Treat your LLM product like traditional software development.

Create, visualize and deploy AI solutions. It is a great platform to learn more about AI. You can use your mobile device to classify images and since it is based on open source, you can view and edit all the code behind each block.