No-code AI platforms are a hot trend that can be leveraged by businesses to help them automate tasks and make data-driven decisions. But which platforms are the best? But before getting into the details, let us understand what a no-code platform is.
What is a No-Code Platform?
There have been multiple attempts over the decades to make programming easier, faster, less technical, and available to a much broader audience. This means that as long as the effort to obtain coding skills is low, computer users who lack coding skills would still be open to using various tools. No-code platforms provide a visual interface for building applications without any coding required. These platforms typically involve drag-and-drop components, pre-built templates, and point-and-click configurations. The goal is to let anyone build digital products, regardless of their technical background.
Why Should We Opt for No-Code AI Platforms?
- Platforms that don’t require coding skills open up opportunities for domain experts to experiment with their ideas and speak more effectively with AI specialists.
- No-code AI solutions are more affordable than customizable AI solutions as fewer data scientists are required to develop ML models.
- No-code platforms are designed to empower broader users, even those without any coding experience. This way, anyone can build applications quickly and easily.
- You can use no-code AI platforms to get actionable insights from data in minutes, rather than waiting for weeks or longer.
- No-code platforms help you develop applications rapidly by allowing you to create code faster for quicker deployment and lesser costs.
Technologies Driving No-Code AI Platforms
Computer vision – Computer Vision for no-code AI is a novel approach to utilizing machine learning for video and image data that doesn’t require coding. This is done by having computer vision algorithms that identify and assess various properties or events. Code-Free Computer Vision AI provides many benefits, such as understanding the environment, detecting obstacles, and finding missing people.
Machine learning – Machine learning can be made more accessible with no-code ML. No-code ML platforms make it possible to deploy AI and machine learning models without any coding. These platforms have a visual interface that is code-free and often uses drag-and-drop. No-code ML platforms are purpose-built for data science and machine learning. They streamline the process of training and deploying models.
NLP – NLP empowers machines with the ability to encode human language and knowledge, allowing them to better understand the human world. With a no-code NLP AI platform, anyone can build their own models or take advantage of the pre-trained NLP engines to automate text-based workflows with the same precision as humans.
No-Code Platforms That Are Democratizing AI
Here is a list of a few major no-code AI platforms that we shortlisted based on the above-discussed technologies.
DeepLobe – DeepLobe is a powerful computer vision and machine learning tool that makes it easy to build and iterate custom models without any coding. With DeepLobe, you can quickly generate rich, embedded data insights from any text, image, or video. It provides image segmentation, OCR, image classification, image similarity, and object detection solutions. You can use pre-built models, or customize them to your needs, and train them to get even better results. DeepLobe is perfect for defect detection, content moderation, and document classification.
Clarifai – Clarifai is a no-code tool built to provide computer vision and NLP solutions. It provides an end-to-end solution for managing unstructured data throughout the entire AI model lifecycle. This includes image, video, and text recognition capabilities that are built on top of an advanced machine learning platform. It also offers accurate and detailed results with a fast API. There are some pre-trained models available for use, such as people, vehicles, and general detectors.
Nanonets – Nanonets offer a wide range of capabilities in the field of computer vision – they have pre-built solutions for many common document types but also offer the ability to create custom models. One particularly useful solution they provide is the ability to build an ID card verification model for any country, format, or language – including perspective transformation, which allows the model to work with images that are taken at an angle.
MonkeyLearn – If you’re looking for an all-in-one solution for data visualization and no-code text analysis, MonkeyLearn is your answer. The platform gives you a complete insight into your data, allows you to build custom visualizations and charts, and even provides ready-made machine learning models. You can also filter insights by data inputs, including custom fields and dates. Sentiment analysis, topic classifiers, etc are a few that you can quickly build on this studio.
RunwayML – RunwayML is a great no-code machine learning platform that makes it easy to train models quickly with its excellent visual interface. It also supports text, image generation, and motion capture. This no-code machine learning platform is excellent for students and creative practitioners from various disciplines.
Primer – For anyone looking for an NLP model builder that is both easy to use and comes with a variety of powerful features, Primer is the perfect solution. With its ability to label, build, customize, and deploy NLP applications rapidly, it is sure to meet all of your needs and expectations.
Pecan – Pecan AI’s code-free predictive analytics tool helps you stay ahead of the competition by giving you foresight into the metrics that matter most to you and your team. With its predictive analytics capabilities, Pecan AI can help you forecast demand, predict churn, and model conversions. The platform’s customer acquisition and retention insights will also help you inform your pricing and packaging decisions, resource planning, and production and distribution processes.
Here, we’ve given you our top seven no-code machine learning platforms that allow anyone, not just developers, to use algorithms to transform data into valuable information and take intelligent action.
Companies of all shapes and sizes are integrating AI into their operations, but businesses that lack specialized AI expertise may have specific challenges when it comes to implementing machine learning processes. Fortunately, a growing number of no-code platforms are emerging to reduce the complexity associated with AI implementation. These tools automate or simplify many of the tasks involved in preparing data for machine learning, cleaning and analyzing data, deploying models and infrastructure, and performing performance optimization.
Despite this, we should be aware that no-code machine learning will not completely replace the need for data scientists to write code. It will not, however, stop business domain experts from being able to test their own hypotheses and ideas for business problems that have been clearly defined. This process can help speed up the transition from concept to production.
Now that you are here, take a look at our no-code machine learning platform, DeepLobe, for your computer vision challenges. Please feel free to contact us for any further inquiries.