No-code ML and AutoML tools are designed to improve the efficiency of everyday ML tasks, as well as to democratize ML. By democratizing ML, non-technical users are empowered with the ability to have ML at their fingertips. These tools make it easy for such users to innovate with ML, allowing them to build and deploy ML models quickly and easily.
Not exactly sure what AutoMLs can do for you? Here’s an article deep-diving into AutoMLs and how they work.
So now that you know you’re going the route of using an AutoML or ML tool for your need (great choice!), the next part is picking the tool. With the number of tools out there boasting various different features, picking the right tool is no easy feat.
Deciding on the right tool depends on your specific needs, and what you would use it for. To help you along your quest for the perfect tool, we’ve compiled a list of the top 10 no-code ML and AutoML platforms.
The AI & Analytics Engine is an end-to-end no-code AutoML platform. The Engine takes users from raw data to model deployment in just minutes, as opposed to days and weeks. The platform enables all users, regardless of their machine learning expertise, to be able to build and deploy models with its easy AI-guided suggestions along each step of the way. Targeted users of the Engine range from individuals and groups, all the way to enterprises. Therefore, there are pricing subscriptions to suit every level of use.
H2O’s Driverless AI is one of the more popular AutoML platforms in the market. And for good reason! The Driverless AI is a highly sophisticated tool that comes with some advanced features. Users like data scientists or machine learning experts would find these features thoroughly enjoyable. That said, the Driverless AI comes with a hefty price tag. Therefore, it is likely not the right solution for an individual user and is more suited for large organizations with data science teams.
Read the comparison article: H2O vs. The AI & Analytics Engine
Amazon’s SageMaker Canvas is a no-code ML platform designed for non-technical users. Users can build, evaluate, and deploy their machine-learning models with a simple and minimalist UI. This tool is used solely for model training and model predictions. For an end-to-end machine learning pipeline, users are able to connect multiple AWS tools together to take them through the whole process from start to end.
Read the comparison article: Amazon SageMaker Canvas vs. The AI & Analytics Engine
Dataiku is a platform that systemizes the use of data and AI, with its mission being to intertwine AI and data such that it becomes a fundamental part of everyday workings. Their specific target audiences are tech experts (such as data scientists, engineers, and architects), business experts (such as analysts), and enterprises. Dataiku may not be the best choice for users with minimal data science knowledge, as some technical knowledge may be required for users to get the most out of the platform and its features successfully.
Read the comparison article: Dataiku vs. The AI & Analytics Engine
Datarobot’s AutoML is an end-to-end tool that makes it easy for users to build and deploy predictive models at speed. Datarobot comes with the ability to monitor and manage your models in real time through a user-friendly dashboard.
Akkio’s AutoML platform is a simple and easy-to-use tool that takes users from data to predictions in minutes. With the targeted users being sales, marketing, and finance operators, the platform enables professionals in these fields to enhance their daily tasks using AI/ML.
Cloud AutoML is Google’s answer to a no-code platform that enables users with limited machine learning expertise to build and train models specific to their needs. Users can train their models on visual, textual, and structure data. Furthermore, with this tool, users can expect to build their own custom machine learning model efficiently in just minutes.
CreateML is Apple’s no-code machine learning tool that lets you build, train, and deploy models directly on your Macs. By using CreateML, users can drastically cut down the time it takes them to carry out ML model training and deployment to a fraction of the time. The tool boasts a drag and drop feature, and makes the process of building models much more convenient and straightforward. Users can train and deploy models to perform tasks like recognizing images, recognizing actions in a video, identifying sounds, or extracting meaning from text.
Prevision.io is an AI platform designed for data scientists and developers to build, deploy, monitor, and manage models quickly and easily so that more data science projects can make it into production at speed. The platform’s intuitive user interface and capabilities enable users to set up in minutes. The platform operates on a pay-as-you-go licensing model, on the Google Cloud Marketplace.
Obviously.ai is a no-code AutoML tool to build and run predictive machine learning models efficiently. The tool’s no-code capability enables users citizen data scientists, business users, and really anyone, to start making predictions without having to write a single line of code. Obviously.ai’s solution solves the pain point of a lack of data science talent. Companies without large data science teams can still leverage ML for predictive analytics.
Read the comparison article: Obviously.AI vs The AI & Analytics Engine
Not sure where to start with AutoML? Reach out to us with your business problem, and we’ll get in touch with how the Engine can help you specifically.
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In this comparison article, we look at two powerful Machine Learning tools, Obviously.AI and PI.EXCHANGE'S AI & Analytics Engine.
In this comparison article, we look at two powerful Machine Learning solutions, Dataiku and PI.EXCHANGE'S AI & Analytics Engine.