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"
I’ve spent a couple of years in a data and analytics startup, that has a consulting focus. As I’ve said elsewhere on this blog, the background in engineering and quality data analysis led me (now it seems inexorably) to this interesting role as a consultant with a focus on data and analytics. While I’ve worked […]Read more "Crosspost: Some Hard Truths About Becoming a Data Scientist"
In my work as senior consultant for businesses seeking to benefit from data, I’ve come across many different hard management problems that impede the progress of change initiatives, and data analytics initiatives. The first among these has to be just the lack of knowledge of capabilities and possibilities from data, which is alleviated somewhat by […]Read more "Crosspost: Data Driven Organizational Change"
Recently, I had the opportunity to finish Stanford SCPD’s XINE 217 “Empathize and Prototype” course, as part of the Stanford Innovation and Entrepreneurship Certificate, which emphasizes the use of design thinking ideas to develop product and solution ideas. It is during this course, that I wrote down a few ideas around the use of data […]Read more "Some Ideas on Combining Design Thinking and Data Science"
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"
Over the past year and a few months, I’ve had a chance to lead a few different data science teams working on different kinds of hypotheses. The engineering process view that the so-called agile methodologies bring to data science teams is something that has been written about. However, one’s own experiences tend to be different, […]Read more "Lessons from Agile in 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"