Being a data-driven company is becoming increasingly common. Each company requires analytics to help them in their decision making, optimizing their processes and also automating tasks. There are excellent tools to store data, visualize data and build machine learning models.
Every year, there are more people who are learning to build machine learning models which are used for businesses, academic purposes or non-profits. Generally, there are multiple models built fora particular use-case. The information regarding these models is stored in an excel file or a text file which is generally lost afterward. If there is a team, the model information is shared through emails and the discussion happens over mail or a chat based client. Basically, to keep track of the model built and to have a discussion is still a cumbersome task.
To make it easier for data scientists, machine learning practitioners, and analytics professional to store their model information and have a discussion is the motivation behind ModelChimp.
Here is preview of ModelChimp
Before starting the process of building ModelChimp, I created a simple survey in typeform and shared it with my circle. This gave me some confidence that people are interested in the idea.
Then created HTMLs and a mocked video using the HTMLs.
This was then followed by creating a landing page with the video embedded in it and features described. The landing page also contains an email sign up which will help me to build a list of beta users and also serve as an indicator of the interest.