User Question: What are the necessary requirements or skills needed to make use of MindsDB? Are there any programming languages attached?
This is related to the accessibility function of MindsDB. Our general objective is to make sure that anyone can use MindsDB. Of course, we cannot start by making it so that everyone can use it, but we try to keep it as simple as possible even from the very beginning.
Right now, we have a native interface that runs on python so you don't have to have a server to be able to use it. All you have to do is run pip3 install mindsdb and, with one line of code, you can do the rest (for how, visit the documentation).
MindsDB generates metadata about your specific machine learning task, that you can visualize through our graphical user interface, MindsDB Scout. If you’d prefer to not visualize your data, you can explore the JSON documentation that we provide.
This is from the developer's end. If you're not a developer, are a beginner developer, or know little about developing, you can still use MindsDB through our graphical user interface, Scout. With Scout, all you need is to have experience using excel. Using it is as simple as uploading an excel sheet or .csv file to make and learn from your predictions.
The reason we made MindsDB open source was to both provide full transparency and open the feedback loop so that we could receive as much feedback as possible from people who have questions that they may not be able to answer because they don’t have a technical background. By providing different ways for people to access MindsDB, we leave room for different personas to be able to take advantage of MindsDB.
Jorge Torres is the Co-founder & CTO of MindsDB. He is also a visiting scholar at UC Berkeley researching machine learning automation and explainability. Prior to founding MindsDB, he worked for a number of data-intensive start-ups, most recently working with Aneesh Chopra (the first CTO in the US government) building data systems that analyze billions of patients records and lead to highest savings for millions of patients. He started his work on scaling solutions using machine learning in early 2008 while working as first full time engineer at Couchsurfing where he helped grow the company from a few thousand users to a few million. Jorge had degrees in electrical engineering & computer science, including a masters degree in computer systems (with a focus on applied Machine Learning) from the Australian National University.