Getting up to speed and using Machine Learning is easy with MindsDB, and even more so with MindsDB Scout. MindsDB is a free, open-source autoML framework to streamline the use of neural networks. It is designed to make it super easy for developers to deploy Machine Learning in their projects.
MindsDB Scout is a free Graphical User Interface that you can run to get the most of the predictive power of Machine Learning. It lets you install, connect, get data visualization, analyze, train and predict Machine Learning models without any line of code.
Connect to where your data lives, analyze, train and ask predictive questions of your data.
The MindsDB GUI is divided into four sections: connection tab, data-sources tab, predictor tab and, last but not least, the query section. Let me run through what each of the sections does, and how that can be of value to you.
This section is all about connecting the Graphical User Interface to wherever your data lives. Here at MindsDB, we understand that data is the most valuable asset of the century - that's why you can choose to connect the MindsDB Scout to your company’s super-secure server, locally on your machine, or if you are just playing around you can connect to MindsDB Cloud; another MindsDB service that lets you experiment with our tool right out of the box.
Here is where the real stuff begins: upload a dataset and after a few seconds you get an analysis of the health of your data. We know there is no global solution for defining what is good quality data, but in our data analysis tab we point out some common probable problems for training ML such as too many NAN values, probable bias or outliers.
This section is all about training the model, which with MindsDB is way easier than it sounds. Click on “Train a model,” pick one of your datasets and define what you want the machine to learn to predict. Once that’s done you can just let MindsDB’s autoML do the rest! This process may take a while depending mostly on the quantity of the data (it could take from minutes to multiple hours) be patient, it will be worth it!
When the model has finished training you can check how well it performed. Some models will perform well, some others not so well - to check the performance of your models go to the predictor preview where you can check if the model is worthy of being trusted for your specific case.
In this section, you can use your previously trained models to get answers. That's right: query a predictor for a prediction. Remember this is not fortune telling, MindsdB GUI will provide you with a confidence score and some other insights for you to keep on mastering ML and improving on your models.
Project manager and Design Thinker with iterative and creative logic. A believer in design and leadership as creative disciplines, well structured and with methodologies, separated from the notion of design as a compendium of techniques and leadership as a talent. Currently making Machine Learning explainable.