I wanted to let people know that my new book Handbook of Regression Modeling in People Analytics is now available.
I first heard of Learning Through Play when I sent my kids to pre-school, but now I realize it’s how all Data Scientists should learn
Everyone is now calling themselves a Data Scientist. No matter what position I am hiring for, that term is on over 80% of the resumes I look at. It has actually made me start to ignore the term because it is not a differentiator of talent any more.
The rate at which data is being generated by business and the world at large is rapidly exceeding the speed at which leaders are equipping themselves to work with data.
The more coding I do, the more sensitive I become to inefficiency. Here are ten hacks I use regularly to try to minimize distractions and keep up my production pace.
I was interested in finding out what it was about someone during that short interaction that determined whether or not someone viewed them as a match. This is a great opportunity to practice simple logistic regression if you’ve never done it before.
Failure to follow these words can put patients’ well-being at greater risk, and can open individuals up to ethical and legal challenges about their decision-making. The three words are evidence based practice.
I am convinced that in the 21st century talent management will be the key differentiator of successful organizations. Within a couple of decades, no matter what measure you use, those with the most advanced approach to the recruiting, development and retention of talent will outperform those who lag behind.
There was once a business executive who kept coming home troubled and distracted. His partner asked him one evening, “What’s the matter? Something’s worrying you.”. “There’s so much data”, he replied, “and I can’t understand it or get my head around it.” “You could try hiring a data scientist”, suggested his partner. So he did just that. Six months later he was still coming home troubled, and when his partner inquired again what was up, he replied: “There’s so much data, and I can’t understand what my data scientist is telling me about it”.
There’s no end of opportunities for Data Scientists out there — you should reflect on how your current situation stacks up