Scholar X 2020 — Part 02

As I write this, I am increasingly confident of my capabilities within the practical aspects of Data Science. I recall myself struggling when I began to write my initial update to Scholar X as I entered this mentor-ship with no prior experience within Data Science and I had to consult my mentor with regard to the “starting point” rather than discussing practical applications. Hence, I am indeed thankful to my mentor for directing me towards the best resources for me to get a head start in this field.

Continuing on from the first 02 months since beginning my mentor-ship, we moved on to discussing potential competitions that we could enter through Kaggle. Before deciding to join a competition, Isuru mentioned that it would be better for me to understand how to work with data structures and obtain a basic understanding of Machine Learning concepts required to generate and improve code. Therefore, I began working on a simple prediction model which focused on predicting what sorts of people were more likely to survive the sinking of the Titanic. I simultaneously referred an introductory Machine Learning course which further developed my understanding and improved my level of preparedness for more complex data sets and competitions.

Source: Kaggle

As I need to accumulate some knowledge and experience in trending areas such as Neural Networks, we decided that we should initially look at a competition that had a majority of its focus on the basics of Machine Learning (before moving onto areas such as Neural Networks). We approached the competition (that we are currently working on) of predicting home selling prices using regression techniques.

Source: Kaggle

I look forward to concluding this competition successfully and try my level best in entering at least two more competitions in order to further develop my understanding and accumulate essential practical experience. In addition, I look forward to the opportunities ahead of me during both, the time left in Scholar X 2020 and the year ahead.