Artificial intelligence and machine learning are two areas of technology that are rapidly developing. They are used in many sectors, including finance, education, and business. Regular activities include the deployment of ML and AI-based models. This makes the process easier and smoother for everyone.
However, artificial intelligence is not used in 25% of organizations according to Analyze. Because all AI and ML models need coding! Building an AI model of your own or hiring a data scientist to do the job, takes significant investment. Many businesses don’t have the necessary knowledge to build an AI model or hire data scientists. They end up using traditional technologies instead.
As a solution to this problem, new ‘No-Code’ platforms have been introduced that allow organizations to execute AI-based work with minimal or no coding.
Top 10 No-Code Machine Learning Platforms
This article will list the best Machine learning platforms for developing models without any programming experience.
It’s an open-source platform that provides machine learning services to business analysts and application integration.
BigML was founded in 2011 to help businesses sort through their data and make data-driven decisions across all industries. It can also build machine learning and deep learning models with no code requirements.
It offers a unique web interface that allows you to upload data, create descriptive predictive models and evaluate machine-learning models. Command Line Interface (also known as bigmler) offers more flexibility. A REST API can also be used as a wrapper in any programming language including Python, Ruby, and Java.
Also read: Top 15 Machine Learning Tools for Developers
2. Teachable Machine
Teachable Machine is a no-code tool for building machine learning models for websites, applications, and other projects. Google offers a web-based application that can teach a computer how to recognize images, sounds, and positions.
It is easy to use for those who don’t have any previous knowledge of machine learning or programming. Teachable Machine is the easiest machine-learning tool that doesn’t require user-friendly no-code when it comes to image recognition.
MonkeyLearn is another no-code machine-learning platform that analyzes language from internal CRM systems, social networks, emails, documents, and online reviews.
MonkeyLearn solutions allow for real-time analysis to instantly access data and make data-driven decisions. This is completely extensible. One can use pre-trained models immediately, or train and can be customized to meet their specific needs and criteria within minutes.
Inbuilt sentiment analyzers and keyword extractors, Feedback, and email intention classifiers which assist users in performing many functions.
MonkeyLearn’s no-code approach to marketing saves time and money. It streamlines operations, boosts marketing and market segmentation, and monitors what customers have to say about the brand on the internet.
4. Create ML
Apple created this no-code ML tool and it can only be used by Mac users for training custom machine learning models. Models can be trained to recognize pictures, extract text, and connect numerical quantities.
These are the analyticsindiamag features of CreateML:
- It can create powerful on-device models and provide user-friendly interfaces. Additionally, it can train multiple models from different datasets within a single project.
- It incorporates an external graphics processing unit with the Mac to improve model training performance. The model’s performance can also be seen on the Mac using continuity with the iPhone camera/microphone.
- You can learn at your own pace. You can save, resume, or extend the training process.
5. Google AutoML
Google AutoML allows users to harness the power of artificial neuro networks to create prediction models using normal text and image data. It also interfaces with Google Sheets and Google Slides to make it easy to get started.
AutoML works entirely in the cloud. Therefore, no infrastructure is needed to get started. Google’s advanced analytics allows you to categorize images, NLP analysis, and AutoML translation.
Google’s years of experience with ML models have meant that their pre-trained models can often be used right out of the box. The UX makes it easy for novice AI users to train bespoke models.
6. Obviously AI
AI is a powerful tool for data-based predictions. It will allow users to go from data collection to machine-learning analysis in just a few mouse clicks. Simply upload a CSV file and select the data analysis you need. You can then instantly see the results, as well as direct queries using Natural Language Processing or natural language understanding.
AI can identify the best method for each use case. Models can be deployed quickly and may be trained faster than other platforms. However, customizations may be slightly less than on other platforms.
The “what-if” scenarios can give you actionable insights in a matter of minutes. This is great for non-programmers. It can be used by marketers and business owners to predict income flow, manage company operations, build a more efficient supply chain and create tailored automated marketing campaigns.
7. Fritz AI
Fritz AI is designed to help smartphone app developers (iOS or Android) quickly and easily integrate machine learning technologies. It does not require any data science expertise. Many connectors are used in software development and require some coding.
Some e-commerce solutions and augmented reality solutions can be created using no-code technology. The model development Studio can be used to create customized services or to access pre-trained models and projects. Fritz AI for mobile is the main product of Fritz AI. Fritz AI For SnapML is its second major product.
8. Google ML Kit
The Google ML kit is another mobile software development tool that requires no code to develop Android or iOS apps. This kit allows you to implement the functionality in a few lines without needing any machine-learning skills.
ML Kit can be used offline to process images and text that must stay on the device. It uses the machine learning algorithms that are underpinning Google’s mobile experiences. It also integrates machine learning models with complex processing lines and makes them accessible through simple APIs, allowing for strong use cases in mobile apps.
RunwayML is a no-code platform that allows machine learning (ML), to be made available to creative producers and students in many fields. It offers user-friendly interfaces for websites that make the process easy and fun.
RunwayML can also be linked to many creative programming and design environments. It works as a plugin for software programs. You can also train your own models to recognize objects in photos and create images.
10. Make ML
MakeML is a tool that uses no code to build neural networks for segmentation and object identification. This technology makes it easy to train. It can manage data sets and training settings as well as markup and model training procedures.
There are many benefits to cloud-based training, including fast GPU instances and a markup tool that makes it easy to generate datasets. It is not necessary to write Python code.
Conclusion — No-code ML platforms
While No-code machine learning platforms have been gaining popularity quickly, they cannot replace custom-built, data-intensive ML models that are created by real data scientists and engineers through coding and practice.
However, it is important to use the right tool to meet your specific needs if you want to create a model on these platforms. We have listed the top 10 No-code machine learning platforms and explained how they work.