I couldn’t sit quietly on my idea for long; the urge to take action grew stronger with each passing day. My mind was fixated on conducting research in Edutech and implementing a more advanced level of personalization than what currently existed. Despite the exciting AI journey that lay ahead, my primary focus was on obtaining a suitable dataset to kickstart my work on personalization. That’s when I stumbled upon a Kaggle competition featuring RIIID’s dataset, and I knew it was the perfect opportunity to get started.

During the early hours, around 4 o’clock in the morning, I found myself in my favorite tranquil bakery, sipping tea and scrolling through social feeds as I often did. As I stumbled upon the Kaggle competition and explored its details, an overwhelming surge of excitement washed over me. Without hesitation, I decided to delve deep into the dataset, determined to craft an algorithm that would push its boundaries and bring about substantial improvements.

My journey began with an immersive dive into research papers that had previously utilized a similar dataset. I was unwavering in my determination to grasp the core concepts, and to enhance my understanding, I sought the collaboration of an old friend who could assist with the mathematical aspects covered in those papers. However, the process of adapting code from Lua to Python presented considerable challenges, leading to a frustrating setback. Thankfully, my spirits were lifted when I discovered the Kaggle community, where like-minded individuals were engaged in collaborative efforts to tackle the algorithmic complexities. Encouraged and undeterred, I persisted in exploring recent papers and diligently worked to implement their cutting-edge techniques into the dataset.

I came across Arshad’s repository, with whom I later collaborated for two years, which implemented a cutting-edge algorithm. Using his work as a foundation, I delved into implementing even more advanced models and extended its support to benefit the community. The response was overwhelming, and the community loved it, resulting in my first-ever gold medal achievement. This success instilled a newfound confidence in me, motivating me to take on more Deep Learning projects.

With this newfound confidence, I took the leap into the world of freelancing on Upwork. The initial phase proved to be quite challenging, as securing projects didn’t always come easy. While there were moments of success where I managed to secure clients, there were also instances of rejection and setbacks. However, I remained steadfast because my true passion resided in Deep Learning – it was not just about monetary gains for me. The sheer joy of working on DL projects fueled my determination to persist, keeping me motivated to push forward despite any obstacles that came my way.

Indeed, those Kaggle projects became my passion, and I wholeheartedly created and shared them on platforms like LinkedIn and Github. Little did I know that this proactive sharing would attract the attention of hiring professionals within the field. They reached out to connect with me and, eventually, I found myself being interviewed for various Deep Learning roles.

The impact of showcasing my work on Kaggle projects turned out to be far-reaching. Not only did it demonstrate my technical expertise, but it also highlighted my unwavering dedication and enthusiasm for the field of Deep Learning. These projects inadvertently allowed me to build a robust and impressive portfolio, which, in turn, opened doors to exciting career opportunities in the realm of Deep Learning.