As the community bonding period ended recently, I started working on my selected project for GSoC but who knew that working on a project, which is out of your comfortable domain will be this demanding.
I was intrigued by the idea of DFFML. Before GSoC, I worked on sources (a part of DFFML that deals with data sources), but that work was rendered complete with the help of my mentor and another fellow student. It required knowledge of basic python and testing. So now for GSoC'19, I had to think of a new project. After a meeting with my mentor, he suggested me to work on adding machine learning models to DFFML, but machine learning was way out of my knowledge boundaries. But then, I stumbled upon an article about how GSoC helps you learn new things not implement what you already are well versed with. So I prepared a proposal and refined it with my mentor.
After getting selected I knew, I had a lot of work to do. I started from async functions and refined my python knowledge, then my college exams started that lead to a little break. But during the exams I had a meeting with my mentor to decide the checkpoints and he was super helpful and supportive for the project. After the exams ended (the current period) I am working on libraries like numpy, pandas and have a goal of implementing linear regression from scratch.