With the evolution of no-code AI, sectors such as web development are advancing while others are just emerging. Now, with these no-code AI platforms, businesses have a chance to explore the technology without needing to hire tech experts or adopting expensive strategies.
NO-CODE PLATFORMS HAVE MADE IT EASY TO CREATE PROGRAMS THAT USE ADVANCED TECHNOLOGIES. THE INTRODUCTION OF THESE PLATFORMS HAS RESULTED IN AN INCREASING NUMBER OF BUSINESSES ATTEMPTING TO USE THEIR CAPACITY TO BUILD AI SOLUTIONS.
With this, visual drag-and-drop tools come into the picture, aiding data scientists in filling the void and making AI less daunting for people with non-technical backgrounds.
This article discusses the top no-code platforms for building AI solutions.
MonkeyLearn
MonkeyLearn is an all-in-one text analysis and data visualization studio that can be used to extract topic, sentiment, intent, keywords, and other information from unstructured text-based data. Automatically tagging business data, presenting actionable insights and trends, and simplifying text classification and extraction processes are just a few of the features. It integrates with Zendesk, RapidMinder, and Google products, with a few others on the way. Also, it is one of the best blog resources for text analysis.
RunwayML
RunwayML is a tool for creators that focuses on creative work that involves dealing with pictures, videos, text, latent spaces, and segmentation masks, as well as motion capture, backdrop removal, and style transfer. They have a Generative Engine, which is a storytelling machine that generates visuals automatically as you write.
Finally
Businesses are increasingly turning to no-code platforms for a variety of reasons. Access to developers and software engineers slows project delivery, partly owing to the ripple impact on workforce management, and this is where technology can help. The unicorn we all want to catch is not only enabling your team to create solutions but also being relevant and competitive in the present context.
For more such updates and perspectives around Digital Innovation, IoT, Data
Infrastructure, AI & Cybersecurity, go to AI-Techpark.com.
2. With the evolution of No-Code AI, sectors such as web development are
advancing while others are just emerging. Now, with these no-code AI
platforms, businesses have a chance to explore the technology without
needing to hire tech experts or adopting expensive strategies.
With the evolution of technology, it is now possible to design complicated
apps without investing a lot of money, waiting months or years, or hiring
several developers.
3. NO-CODE PLATFORMS HAVE MADE IT EASY TO
CREATE PROGRAMS THAT USE ADVANCED
TECHNOLOGIES. THE INTRODUCTION OF THESE
PLATFORMS HAS RESULTED IN AN INCREASING
NUMBER OF BUSINESSES ATTEMPTING TO USE
THEIR CAPACITY TO BUILD AI SOLUTIONS.
With this, visual drag-and-drop tools come into the picture,
aiding data scientists in filling the void and making Artificial
Intelligence (AI) less daunting for people with non-technical
backgrounds.
4. Lets Understand more about the top no-
code platforms for building AI solutions.
Clarifai - Clarifai, founded in 2013, is an NLP and Computer Vision tool
that provides an end-to-end solution for modeling unstructured data
throughout the AI lifecycle. Image, text, and video recognition solutions
are built on a cutting-edge machine learning platform that can be
accessed through API, device SDK, or on-premise.
5. CreateML - Apple has been allowing developers to use transfer
learning to create bespoke machine learning models since 2018.
The app enables users to create models for object and activity
detection, as well as picture, sound, video, text, and tabular
models.
Google AutoML - AutoML is the Google package star, which works like
CreateML but in the cloud. Sight (Vision and Video Intelligence, the latter
in beta) and Language (NLP & Translation), as well as structured data
functions (Tables), are currently included in the model package.
6. DataRobot - The DataRobot enterprise AI platform modifies data
science and automates the whole AI development, deployment, and
maintenance process. It was founded in 2012, focusing on predictive
models, powered by open-source algorithms, and offered in the cloud,
on-premise, or as a fully-managed AI service.
Levity - Levity focuses on text, image, and document categorization and
allows users to train unique models on their use-case-specific data, and is
suitable for companies of all sizes. A human-in-the-loop option is included in
custom models and processes, giving users complete control over the model,
which requests inputs when it is unsure and learns from interactions.
