Tag: data science

Every emerging technology is accompanied by CEOs champing at the bit. Artificial Intelligence, or AI, is no different. The C-Suite is throwing “AI” into as many conversations as possible to appease shareholders and give off the appearance of a technologically savvy company. While organizations love to embrace new technologies,...

An important part of every data science professional’s growth journey is evolving from data preparation and model training to owning the entire machine learning development cycle. The full cycle includes data ingestion, data cleaning and preparation, feature engineering, model training, model evaluation, model deployment, model serving, and model maintenance....

As a data scientist, I find it hard to believe that anyone would trust their financial portfolio to an advisor who doesn’t understand the basics of statistics and probability. Yet, how many investors do you know who blindly trust their advisor or financial planner? How many of those advisors...

Whether it is Alexa answering a question or Elon preaching self-driving cars, business leaders see exciting machine learning use cases everywhere they look. The hype around artificial intelligence (AI) and machine learning (ML) is staggering. So much of the mainstream discussion centers around these exciting applications, but they often...

Introduction In a world of infinite options, choosing the appropriate graduate school to prepare you for a career as a data professional can be paralyzing. While graduate school is not the best option for everyone, it is a path that warrants consideration for many. Within the landscape of technical...

I first ordered The Hundred-Page Machine Learning book back in May and am only just now finishing it up. In COVID-time, that was about 10 years ago. As you might have inferred, this book is NOT a quick read. What it lacks in easy reading, it makes up for...