Machine Learning, Deep Learning, Neural Networks and Artificial Intelligence AND NOW Crypto/Blockchain/NFTs!
To introduce myself:
Hello from Christopher Himmel, business data analyst and Data Science/Machine Learning/Deep Learning/Artificial Intelligence instructor and practitioner. The Data Scientist job description, coined by DJ Patil and Jeff Hammerbacher in 2012 is very new. I arrived at Data Science in an indirect manner.
A short 28 years ago, I published my first papers with Dr. Gary May at Georgia Institute of Technology in Neural Networks. The subject matter would be considered the foundation of today's Machine Learning and Deep Learning techniques. In fact, the topic of these papers was in comparing the accuracy of Statistical Models to Neural Network models, applied to Semiconductor Manufacturing processes. Those papers have since been referenced/cited 385 times and counting, four as recent as 2019.
Since that time, having finished my MS in Electrical Engineering, I have been in the Information Technology/Business world working to automate processes mostly in the construction, retail and financial world. I followed my father's footsteps as a developer, and programming computers had been my passion since I was 8 years old. My first home computer was the Radio Shack TRS-80. Note release date for that model, August, 1977.
After graduating from GaTech, through 2005 (considered the Dark Ages of AI), I was constantly drawn back to the concept of modeling cognitive processes. I enjoyed reading and studying psychology and related topics, and my professional life moved towards Business Intelligence, Data Warehousing (organizing big data into a summarized cube) and Analytics. The ultimate goal for Business Intelligence was, in an automated fashion, actioning back into the transactional business systems from structured big data. This control system feedback style mirrored the iterative backpropagation process used in training my artificial neural networks in my research.
Fast forward to 2011, I found myself in the San Francisco Bay Area. I soon became more involved in the growing Data Science world by attending dozens of meetups, seminars, courses, bootcamps and conferences readily available in San Francisco and Silicon Valley. I was completely absorbed back into the Machine Learning world, involving myself in every way possible, while continuing to work in the retail industry as a programmer and analyst.
Currently, I am expanding the application of what is now my passion, to my "day job" at Intuit, participating in a Data-centric group by presenting on current topics in Machine Learning. I am also pulling together different applications of Machine Learning for immediate application. I created a nine week lecture series on Machine Learning for the mentoring group Data Science Dream job, taking a beginner in Data Science through to running your own models in Python. I am also instructing an Advanced Machine Learning Certification course for SimpliLearn, expanding my reach in spreading the latest in Machine Learning methodologies!
Thank you for your short attention, and I hope you enjoy reading further as I expand the world of Data Science by sharing some of my favorite articles/videos/graphics. And of course I will be promoting my own work, from projects I am involved in or doing myself, to coursework I create for a better understanding of the engineering and math behind Machine Learning.
MSEE Georgia Tech, c/o 1994
By the way, watch my interview with Humans of Data Science here!