Top 12 ‘No-Code’ Machine Learning Platforms In 2021

By 2024, as much as 65% of application development will be done on no-code/low-code platforms, according to a Gartner Magic Quadrant report. The no-code application platforms have shown a lot of promise and productivity gains. Such platforms help organisations to automate and digitise processes with cloud-based mobile apps.

Below, we have curated the top 12 no-code machine learning platforms in 2021.

(The list is in alphabetical order)

1| BigML

About: BigML is an open-source no-code tool that provides commoditised machine learning as a service for business analysts and application integration. It can build a machine learning or deep learning model with just 3-4 clicks. The tool includes:

  • Web interface, which helps users to upload a dataset, make a descriptive predictive model as well as evaluate the machine learning model.
  • Command Line Interface, also known as bigmler, allows more flexibility than the web interface.
  • REST API that can be used as a wrapper in any programming language including Python, Ruby, and Java.

Know more here.

2| Create ML

About: Create ML is a no-code machine learning tool by Apple to create and train custom machine learning models on Mac. Users can train models to perform tasks like recognising images, extracting meaning from text, or finding relationships between numerical values.

Some of its features are:

  • Build and train powerful on-device models with an easy-to-use app interface.
  • Train multiple models using different datasets, all in a single project.
  • Preview the model performance using Continuity with iPhone camera and microphone on Mac, etc.
  • Use an external graphics processing unit with the Mac for better model training performance.
  • Pause, save, resume, and extend the training process.

Know more here.

3| Data Robot

About: DataRobot is a popular end-to-end enterprise AI platform for fast and easy deployment of accurate predictive models. DataRobot automated machine learning software supports all the steps needed to prepare, build, deploy, monitor, and maintain powerful AI applications at enterprise scale.

Know more here.

4| Fritz AI

About: Fritz AI is the machine learning platform for iOS, Android, and SnapML in Lens Studio. One can use the model development Studio to train custom solutions, or jump right in with pre-trained models and projects. Fritz AI for mobile and Fritz AI for SnapML are the two key products of Fritz AI.

Know more here.

5| Google Cloud AutoML

About: Google Cloud AutoML is a no-code tool for training high-quality custom machine learning models with minimal effort and machine learning expertise. The tool enables developers with limited machine learning expertise to train high-quality models specific to their business needs. Developers can build their own custom machine learning model in minutes. You can use AutoML to build on Google’s machine learning capabilities to create your own custom machine learning models, and then integrate the models into your applications and web sites.

Know more here.

6| Google ML Kit

About: Google ML Kit is a mobile software development kit that brings Google’s machine learning expertise to Android and iOS apps. With this kit, one can implement the functionality in just a few lines of code, without the need of machine learning expertise. Some of its features are:

  • ML Kit works offline and can be used for processing images and text that need to remain on the device.
  • It takes advantage of the machine learning technologies that power Google’s own experiences on mobile.
  • It is a combination of machine learning models with advanced processing pipelines and offers these through easy-to-use APIs to enable powerful use cases in the apps.

Know more here.

7| MakeML

About: MakeML is a no code tool for creating object detection and segmentation neural networks. The tool is built to make the training process easy to set up. It is designed to handle data sets, training configurations, markup, as well as training processes in models. The advantages include:

  • Fast training in the cloud on GPU instances
  • Convenient markup tool for creating Datasets
  • No need for Python code.

Know more here.

8| Microsoft Azure Automated Machine Learning 

About: Automated ML in Azure Machine Learning is a no-code tool which can be used to train and tune a machine learning model. It democratises the machine learning model development process, and empowers users to identify an end-to-end machine learning pipeline for any problem. You can use Azure automated learning to:

See Also

ClearML: Zero Integration MLOps Solution

  • Implement ML solutions without extensive programming knowledge
  • Save time and resources
  • Leverage best practices in data science
  • Provide agile problem-solving

Know more here.

9| Obviously AI

About: Obviously AI is a no-code machine learning tool that makes data science effortless by enabling anyone to instantly run accurate predictions as well as analytics on their data by asking questions in natural language.

Know more here.

10| RunwayML

About: RunwayML is a no-code platform that makes machine learning (ML) techniques accessible to students, and creative practitioners from a wide range of disciplines. RunwayML also connects to a variety of creative programming and design environments and integrates with software applications as a plugin. You can also train your own models to generate images and identify objects in images.

Know more here.

11| SuperAnnotate

About: SuperAnnotate is an end-to-end platform to annotate, train and automate computer vision pipelines. With the help of this tool, one can scale annotation and computer vision projects of all sizes using the smartest tools, robust data management systems as well as outsourced services.

Know more here.

12| Teachable Machine

About: Teachable Machine is a no-code tool to create machine learning models for your sites, apps, and more. The web-based tool can be used to train a computer to recognise images, sounds, and poses 

Know more here

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