These Tools Let You Generate Machine Learning Models Without a Programming Language

In the era of modern technology, the application of machine learning (ML) is one of the essential elements. In general, ML technology is used to reduce the duration and work process in measuring analysis and accuracy. As in data analysis, for example, ML technology is usually applied to produce accurate insights in a short time. With complex computational processes, ML technology can provide the data insights needed, from visualization to predictive models. The complexity of ML technology is run through a programming process (coding) which of course requires special skills. Even so, for those of you who don't have the coding skills to command ML to analyze the data you want, the well-known cloud solution platform, Amazon Web Service (AWS) has the solution. This is Amazon SageMaker, a tool that allows anyone to generate ML-based predictive models without the need for a programming language. What's it like?

Amazon SageMaker is one of the many cloud computing solutions that AWS offers. Seeing the ever-increasing need for ML technology deployments, Amazon SageMaker is available to anyone who needs to model analysis and predict data generated from ML “intelligence” with a high degree of accuracy, without having to write individual programming code. In the official website, the Amazon SageMaker infrastructure can be used by the following functions such as; Business Analyst, MLOps Engineer, to Data Scientist.

Sound fantastic? Let's explore first the things that a Business Analyst needs in full. Broadly speaking, Business Analyst requires programming tools, statistics, software engineering, data wrangling, and also data visualization. With Amazon SageMaker Canvas, the company's Business Analyst is able to cut these hard skills and obtain accurate prediction and analysis models simply by entering the dataset you want to process.

On paper, all the capabilities to build, train, and deploy datasets to generate predictive models can be provided by the latest tools that just launched in November 2021 without any coding. Amazon SageMaker Canvas has four pillars of features and services that you can take advantage of when you officially peddle AWS cloud solutions. The four pillars in question are; ease of access and preparation of data to be processed into ML, built-in AutoML to generate accurate predictions, features for sharing ML models and collaborating with Data Scientists, and last but not least, pricing that can be adjusted based on usage.

Interested in learning more about Amazon SageMaker? AWS Indonesia again through the #StartupUntukNegeri program, together with DailySocial.id, will hold a webinar that will introduce more details about implementing machine learning through AWS cloud solutions, which of course will also be introduced further about Amazon SageMaker Canvas in a webinar titled #StartupUntukNegeri: “Steps Easy to Create Competitive Advantage by Utilizing Machine Learning” which will be presented by Riza Saputra, Solutions Architect, Amazon Web Services Indonesia on April 26, 2022 at 19:00 WIB.

So that you don't miss it, just go ahead register yourself on this page and see you at the #StartupUntukNegeri webinar presented by AWS Indonesia and DailySocial.id