#Deeplearning is one of the most important skills data scientists can have these days. That said there are numerous other skills that get passed over in the search for good data scientists. I’ll attempt to discuss some of them in this series of tweets. — Rajesh S (rexplorations) (@rexplorations) July 18, 2018 This post stems […]Read more "Achieving Explainability and Simplicity in Data Science Work"
This year, 2017, has been quite a busy year for artificial intelligence and data science professionals. In some ways, this is the year when AI truly began to be debated and discussed, from frameworks and technologies to ethics and morality. This is the year when opportunities for AI-driven improvement in businesses began to be examined […]Read more "Key Data and AI trends in 2017"
One of the more interesting mental models of machine learning I’ve come to understand in the last month or so, is the “five tribes of artificial intelligence” model popularized in “The Master Algorithm” by Pedro Domingos. To summarize in a phrase, the master algorithm is that approach which can uncover all possible insight from data […]Read more "Andrew Ng’s DeepLearning.AI (Coursera) Certification"
As of mid-2017, I’ve spent almost two years in the big data analytics and data science world, coming from 13 years of diverse work experience in engineering and management prior. Starting from a professional curiosity, it has taken me a while to develop some data science and engineering skills and hone key skills among these […]Read more "Pervasive Trends in Big Data and Data Science"
Although the data science and big data buzzwords have been bandied about for years now, and although artificial intelligence has been talked about for decades, the two fields are irrevocably inter-related and interdependent. For one thing, the wide interest in data science started just as we were beginning to leverage distribute data storage and computation […]Read more "The Expert System Anachronism in the Data Science and AI Divergence"