Understanding No-Code AI And Top No-Code Machine Learning (ML) Tools For Some DIY ML Projects

AI applications have made their way into almost every sector, yet; businesses fail to adopt them. According to Forbes, 83 percent of companies think AI is a strategic priority for them, yet there is a shortage of skilled data scientists. This is not only because AI solutions and expertise are expensive but also because firms lack the infrastructure to support these solutions.

Companies are increasingly deploying AI and machine learning models using no-code AI, a no-code development platform with a visual, code-free, and typically drag-and-drop interface. Non-technical people may quickly classify, evaluate, and develop accurate models to make predictions with no coding AI. 

There is no code. Individuals and corporations may now experiment with AI and machine learning more efficiently. These solutions assist businesses in swiftly and affordably adopting AI models, allowing their domain experts to benefit from cutting-edge technology.

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No-code machine learning offers many benefits such as:

  • It helps businesses save money by automating processes. When companies can have their business users construct machine learning models, they require fewer data scientists.
  • No-code solutions reduce the number of requests for data scientists to complete simple tasks by allowing business users to handle such requests themselves.
  • Writing code, cleaning data, categorizing, structuring data, training, and debugging the model are all necessary steps in creating unique AI solutions. According to studies, minimal code/no-code solutions can save development time by 90%. 

Above all this, no code AI helps business users leverage their domain-specific experience and quickly build AI solutions.

Some of the cool no-code machine learning tools are mentioned below:

Google’s AutoML 

This platform offers vision (image classification), Natural Language, AutoML Translation, Video Intelligence, and Tables among the machine learning solutions. By delivering out-of-the-box support for extensively validated deep learning models, AutoML on the cloud eliminates the need to know transfer learning or the design of a neural network. This allows developers with little or no machine learning experience to train models tailored to their specific use cases.


It is a developer tool that allows users to create object detection and semantic segmentation models without writing a single line of code. It offers an iOS developer macOS software for creating and managing datasets (such as performing object annotations in images). They also feature a dataset store with some free computer vision datasets that may be used to train a neural network in a matter of seconds.

Teachable Machines

It is another Google machine learning platform that doesn’t require any coding. Teachable Machines allows easy training of models to identify images, sounds, and poses straight in your browser. Users can teach your model by simply dragging and dropping files. They can also utilize the webcam to create a quick and dirty dataset of images or sounds.


Apart from model training, data processing takes up a significant amount of time while building machine learning projects. SuperAnnotate is AI-powered annotation software that boosts your data annotation process by utilizing machine learning skills. Users can instantly annotate data using their picture and video annotation tools, including built-in prediction models.

Runway ML 

This no-code platform offers tools to create synthetic photos and videos, edit material, and animate faces using AI. The company’s platform, built for creatives, allows them to use machine learning to streamline their job.


BRYTER is a service automation company that helps businesses create virtual assistants, chatbots, self-service tools, and other applications. The company’s platform offers a scalable compliance solution for legal, tax, HR, and security services, which are often conducted manually and are difficult to scale.

While no-code AI platforms can’t completely replace a trained team of computer scientists, they provide a viable alternative for businesses wishing to automate parts of their robotics processes (RPA). While most no-code apps are currently confined to prefabricated sets of industry-agnostic operations, as these businesses build increasingly robust plug-and-play AI algorithms, the depth and breadth of options are expanding.


  • https://towardsdatascience.com/top-8-no-code-machine-learning-platforms-you-should-use-in-2020-1d1801300dd0
  • https://www.nanalyze.com/2021/04/no-code-platforms-machine-learning/
  • https://research.aimultiple.com/no-code-ai/

Tanushree Shenwai is a consulting intern at MarktechPost. She is currently pursuing her B.Tech from the Indian Institute of Technology(IIT), Bhubaneswar. She is a Data Science enthusiast and has a keen interest in the scope of application of artificial intelligence in various fields. She is passionate about exploring the new advancements in technologies and their real-life application.

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