Summary: Reinforcement Learning (RL) is going to be critical to achieving our AI/ML technology goals but it has several barriers to overcome. While reliability and… Read More »Can Reinforcement Learning Break Through in 2020
The history of Database management systems could be interpreted as a Darwinian evolution process. The dominance of relational databases gives way to the data warehouses… Read More »It's time for Time-series Databases
Here is another resource I use for teaching my students at AI for Edge computing course. I like this resource because I like the cookbook… Read More »Data science cookbook style code reference in Python for beginners
“When I think back on all the crap I’ve learned in high school, It’s a wonder I can think at all” – Simon and Garfunkel, Kodachrome… Read More »I (kind of) Liked New Math
As a data scientist in an organization you frequently find yourself in a couple of situations: you have a dataset, you want to extract some useful… Read More »Not tools, focusing on problems: a project cycle in data science
In a recent blog I stated that “Crossing the AI Chasm” is primarily an organizational and cultural challenge, not a technology challenge. That “Crossing the… Read More »Wanna Build an AI-powered Organization? Start by Getting EVERYONE to “Think Like A Data Scientist”
Through exposure to the news and social media, you are probably familiar with the fact that machine learning has become one of the most exciting… Read More »Tech Talk: Sebastian Raschka’s take on TensorFlow 2.0 and the new edition of his widely acclaimed Python Machine Learning book
The picture below is from the article Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey, posted here. Authors: Giang Nguyen,… Read More »Machine Learning Technical Landscape
In a recent blog, I described the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders as an ontological reference. I explained how this… Read More »Event Conceptualization & Distribution Modelling
You can always learn a lot from the papers presented at NeurIPS There is some good analysis already on the web. From Chip Huygen –… Read More »NeurIPS 2019 – analysis of papers by themes
