Unlocking the Power of Time Series Data in Machine Learning
As a budding Machine Learning enthusiast with a background in Physics, my journey into this field was driven by a passion for coding and data science. Data, in all its forms, intrigued me, and the idea of delving deep into complex algorithms and writing thousands of lines of code excited me like nothing else.
Little did I know that my career path would lead me to the realm of time series data, a unique and fascinating aspect of data science. While I may not have cared much about the types of data initially, my professional journey steered me towards working with time series data.
In different industries, such as SpaceX, Netflix, or Tesla, the nature of the data you work with can vary significantly. From signal processing at SpaceX to NLP and recommendation systems at Netflix, and computer vision at Tesla, the type of data you engage with is often dictated by the industry you are in.
My journey from Physics to Engineering exposed me to the world of signals, a fundamental aspect of engineering. Every setup we work with, every piece of information we extract, ultimately boils down to dealing with signals. This intricate world of signals forms the backbone of various industries, shaping the trajectory of data scientists and machine learning experts.