There’s a process for solving business problems via machine learning. If you Google “learn machine learning,” you’ll find a bunch of guides, online courses, and such that walk you through the coding languages of ML and the processes it takes to solve data predictions. You conclude it takes a lot of time to learn technical machine learning.
And it does. Mastering ML is super hard and requires investment if you want to apply it to solving problems for your business. However, something that doesn’t come up that often in the Google SERP, is “no-code machine learning.” Compared to the keyword “learn machine learning,” which has the volume of around 2K searches/month (according to Ahrefs), “non-technical machine learning” Ahrefs doesn’t even have enough data to get an accurate search volume — meaning the search volume is very low.
The question you’re trying to answer often comes with loopholes and turns into a string of jumping between engineers and trying to learn code. There are communication barriers, you can’t commit enough time to the data science process, and maybe you consider breaking up with your data altogether.
We believe that this relationship with data needs to change. There needs to be a spark.
Over the years, working with business users we have started to learn that:
- Traditional data science is too complicated for the average non-tech team member.
- Non-technical users request a team of engineers to solve problems that could take weeks to answer.
- The user can’t visualize a data output and has to create their own charts and graphs to communicate their findings.
All of these things can be fixed by introducing no-code data science into your relationship.
No-Code Machine Learning
No-code ML simplifies this process into this:
- drag and drop and upload data
- click on auto-learn
- download predictions.csv and machine learning model.
- visualize insights of machine learning model
A New Approach to Machine Learning
With no-code machine learning you:
Become data-driven without a data science team — Most companies that want to be data-driven don’t often have a data science team or cannot scale one. This means finding data science talent and shifting around a budget to offer salaries to data scientists or analysts become common roadblocks in their day-to-day work. No-code ML tool, can offer a great alternative and provide results in seconds rather than days/weeks.
No-Code Machine Learning is Cheaper, Simpler, and Quicker
As you can see, the no-code machine learning process is much shorter and simpler than the traditional process which also requires the learning of technical skills. With a no-code machine learning platform, you can do all of the same things — except without the expensive team of data scientists and improve business and product decisions quicker.
check out : https://www.scoopml.app
ScoopML is an AI assistant for data scientist which improves his productivity.