The low-code platform improves the speed and quality of application development, integration, and data visualization. Instead of building forms and workflows in code Low code platform It provides a drag-and-drop interface for designing screen, workflow, and data visualizations used in web and mobile applications. Lowcode integration tools support data integration, data preparation, API orchestration, and connectivity to popular SaaS platforms. If you’re designing dashboards and reports, there are many low-code options for connecting to a data source and creating a visualization of your data.
If you can do that in your code, maybe Low code or no code technology It can help Accelerate the development process Simplifies continuous maintenance. Of course, you need to evaluate whether the platform meets functional requirements, costs, compliance, and other factors, but low-code platforms are between building your own or purchasing software as a service. Provides options in the gray area (SaaS) solution.
But are low-code options the only way to develop applications, integrations, and visualizations better and faster? What about a low-code platform that speeds up and simplifies with more advanced and new features?
We searched for and prototyped low-code and no-code platforms that our tech team could do. Spikes and experiments It has a machine learning function. I focused primarily on low-code application development platforms and looked for machine learning capabilities to improve the end-user experience.
Here are some of the things I learned on this trip.
Are you a data scientist looking for low code capabilities to try out new machine learning algorithms and support? modelops Is it faster and easier than coding in Python? Maybe you are a data engineer who wants to focus on data manipulation and connect data to machine learning models while discovering and validating new data sources.
Data science and modelops platforms, etc. Alteryx, Dataik, DataRobot, H20.ai, KNIME, RapidMiner, SageMaker, SAS, When Many others It aims to simplify and accelerate the work performed by data scientists and other data professionals. It has comprehensive machine learning capabilities, but is more accessible to professionals with data science and data engineering skill sets.
Here’s what Dr. Rosalia Silipo, Principal Data Scientist and Head of Evangelism at KNIME, told me about low-code machine learning and AI platforms: “The AI ​​low-code platform is an effective alternative to traditional AI script-based platforms. Low-code solutions remove coding barriers to reduce the learning time required for tools and new ideas, paradigms, and strategies. , Optimize, and increase the time available to try out the data. “
There are multiple platform options, especially for software developers who want to take advantage of machine learning capabilities in their applications and integrations.
These low-code examples are aimed at developers and data scientists with coding skills and can help accelerate the experimentation of various machine learning algorithms. MLops platform Target developers, data scientists, and operations engineers. The MLops platform aims to make effective use of machine learning devops to simplify the management of machine learning model infrastructure, deployment, and operations management.
A new group of no-code machine learning platforms is aimed at business analysts. With these platforms, you can easily upload or connect cloud data sources to experiment with machine learning algorithms.
We spoke with Assaf Egozi, co-founder and CEO of. NugataWhy a codeless machine learning platform for business analysts can be a game changer for large companies with experienced data science teams. He tells me: “Most data users in an organization do not have the skills needed to develop algorithms from scratch or effectively apply autoML tools. Rather, these data consumers, or citizens. We need to provide data analysts with an easy way to integrate advanced analytics into their business processes. “
Andrew Clark, CTO and co-founder Monitor UrsI agreed. “It’s exciting to make machine learning more familiar to the business. Trained data scientists and engineers with expertise in model commercialization aren’t enough to meet the demands of the business. The code platform provides a bridge. “
Low code democratizes and accelerates machine learning experiments, but still requires disciplined practices, alignment with data governance policies, and bias reviews. Clark said: “Companies need to see low code as a tool to benefit from AI / ML. Considering the business visibility, control, and management of the model needed to make credible business decisions. They shouldn’t take shortcuts. “
Now let’s focus on the low-code platform that provides machine learning capabilities for software developers. These platforms choose machine learning algorithms based on their programming model and the type of low-code functionality they expose.
This is not a comprehensive list. One list of low-code and no-code machine learning platforms Also the name Create ML, MakeML, MonkeyLearn Studio, Obviously AI, Machine to be taught, And other options.See also 2021 no-code machine learning platform When No-code machine learning platform.. The possibilities increase as more low-code platforms are developed or partnered with machine learning capabilities.
As low-code platforms continue to differentiate feature sets, we expect to add more machine learning capabilities needed for the user experience they enable. This means more text and image processing to support workflows, portfolio management platform trend analysis, CRM and marketing workflow clustering.
However, large-scale supervised and unsupervised learning, deep learning, and model ops must be integrated using specialized data science and model ops platforms. More low-code technology suppliers may partner to support integration or provide on-ramp to enable machine learning capabilities on AWS, Azure, GCP, and other public clouds.
It remains important that low-code technology makes it easy for developers to create and support applications, integrations, and visualizations. Whether your low-code platform invests in its own AI capabilities or offers integration with third-party data science platforms, raise the bar and expect more intelligent automation and machine learning capabilities.
Copyright © 2021 IDG Communications, Inc.
How Lowcode Development Enables Machine Learning
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