Are you familiar with non-technical machine learning, also known as no-code machine learning? No-code machine learning is set to create a new wave in enterprise startups by reducing the amount of time and money spent on mundane coding tasks. One of the main aims of no-code development is to create an environment for accessible non-technical machine learning. Learn why no-code machine learning is trending and how you can use a SaaS platform like Skyl.ai to become a machine learning professional who can build models in minutes without coding expertise.
Why No-Code Development?
In any organization, there are multiple requests directed to the IT department for implementing new applications or fixing bugs in existing apps. This creates a huge task backlog which may take several weeks or even months to complete. And, once these tasks are complete, a new set of requests accumulates in the pipeline, creating a never-ending cycle. No-code machine learning to the rescue!
By implementing a non-technical machine learning platform, a layman can create a complete application without extensive programming knowledge, freeing up IT team members for other tasks.
Difference Between Traditional and No-Code Machine Learning
The traditional machine learning process involves several steps, including data collection; data preparation; selecting, training, and evaluating the model; parameter tuning; and so on. It is a complex process.
No-code machine learning simplifies this process and eliminates DevOps and software engineering steps. No-code machine learning does not require that team members master technical machine learning programming.
Why Should You Master No-Code Machine Learning?
:Learning to write machine learning codes is a time-consuming process that takes dedication and commitment. With a no-code platform, machine learning is no longer limited to programmers. It empowers product managers and business analysts with predictive analytics, which enables them to perform complex analysis in a code-free environment.
Benefits of No-Code Machine Learning Platforms
No-code helps people solve real-life problems without burdening the tech team with too many requests. This saves a few hours each day that can instead be spent on implementation by the IT team, resulting in enhanced employee productivity and overall efficiency. Apps built by citizen developers foster smooth operations within a company as per a recent study. The main use of no-code development is to ensure workers follow standard procedures during the tenure of a project.
The process of building apps is quicker using pre-built modules. It takes less time to build due to the automated testing process.
Easy Change Management
With traditional hand-coding, the problem is that you can’t really change a functionality or a feature at the drop of a hat—especially when the coding language is foreign to you. A no-code development platform is the exact opposite.
Offset IT Tasks
Companies are taking a long and hard look at no-code development as a means to offset IT tasks and ensure that their IT departments aren’t clogged with requests.
Ability to Address the Scarcity of Data Scientists
Data scientists are pricey and difficult to come by. Why go through the trouble and expense of finding one when citizen developers who already work for you can build models? In 30 percent of small and medium-sized companies, no-code machine learning professionals collaborate with IT teams to give a final shape to apps.
No-code machine learning saves costs for developing and maintaining software. Companies are no longer required to hire programmers with strong coding skills. Instead, they can make use of in-house talent to complete these tasks.
How Skyl.ai Can Be Used as a No-Code Platform
Skyl.ai is a scalable, easy-to-use, no-code machine learning platform that reduces implementation costs and solves data issues. Here’s how Skyl.ai allows business users without formal coding skills to optimize day-to-day operations.
1. No-Code Data Collection
Skyl.ai provides various methods of data collection, such as API or collaboration jobs, but the most convenient and easy way to create your dataset is through the CSV upload feature. Design your dataset schema through the guided and templatized workflow of Skyl.ai, upload your CSV file, and your dataset is complete.
2. No-Code Model Training
Train models without coding using Skyl.ai’s ready-made, fine-tuned, state-of-the-art neural network architecture. You also have the flexibility to tune the hyperparameters, including the number of epochs, learning rate, and so on.
3. No-Code Model Deployment
Setting the model deployment pipeline consumes a lot of time and resources in the machine learning life cycle, but Skyl.ai offers a one-click model deployment feature that streamlines the entire process. It is also possible to roll back a model with the click of a button. No coding required.
Do you think machine learning is right for your business? Continue exploring the benefits of no-code machine learning.