Hi, I am currently a Machine Learning Scientist at a small biotech startup where I develop and implement new machine learning algorithms using various methods including deep learning. I obtained a PhD in Computational Neuroscience which gave me experience in Machine Learning, developing new algorithms to analyze brain data and build models with neural networks. I have more than 10 years of experience analyze data and programming in Python.
As the company I currently work for is relatively small, I have many hats from data and ML scientist to MLops and ML Engineer. I manage tasks ranging from basic data analysis for other teams, doing research and implementing Machine Learning algorithms and simulations, setting up the code infrastructure and best practices in ML development, and maintaining MLops tools required for our research.
I have experience teaching classes in college, from Excel classes to Introduction to Modeling in Neuroscience, and I have mentored numerous students throughout my career in academia. I prefer a top down approach where you first develop an intuition about the concept you want to learn, and then we go into the details of how it works. For example, if you want to learn how PCA works, we will first build a graphical intuition that a PCA is merely translating and rotating the axes to fit the data and then go into the math and see how it relates to the intuition. See Jeremy Howard's top-down approach to teaching, his course Practical Deep Learning for Coders is a perfect example.