If you’ve been reading the Sharp Sight blog for a while, you’ll know that I’m a big fan of elite performers: Navy SEALs, grandmaster chess players, elite athletes, etcetera. I want to understand how elite performers operate across multiple disciplines, so that I can find what makes them special. The techniques. The training methods. The … Read more
Data visualization is extremely important in data science. Although you often hear about the importance of data manipulation (i.e., “80% of data science is data manipulation”), data visualization is just as important. I explained why in a recent blog post about why you need to master data visualization. That blog post has a detailed explanation … Read more
One of the biggest questions from data science students is what to focus on. All of us have limited time and there is a lot to learn in data science. Many overzealous students throw caution to the wind, and immediately try to learn advanced topics like machine learning. As I’ve said many times, this is … Read more
If you’re interested in data science and want to become a data professional, you’re probably going to need to make a choice. I think that the industry is going to split – and in fact, it probably already has. This split that I’m referring to is the divide between the top performers – the top … Read more
Here at Sharp Sight, we teach data science. And in particular, we show people how to master data science extremely fast. Exceptional results, as fast as possible. Our training methodology borrows heavily from elite performers and “ultra learners,” wherever we can find them. But our promise of “exceptional results, as fast as possible” sometimes confuses … Read more
Here at Sharp Sight, I frequently use the word “fluent” to describe an ideal skill level with data science. When you join our courses, our goal is to help you become “fluent” in data science, or “fluent” in a particular skill. We want to help you become fluent in data science as fast as possible. … Read more
One of the common questions that I get from my readers is about “big data.” This is particularly true of beginners, who frequently read or hear the term “big data,” and think that it’s extremely important, and that being able to work with big data is necessary for a job in the data industry. For … Read more
This tutorial will show you how to use the NumPy mean function, which you’ll often see in code as numpy.mean or np.mean. It will teach you how the NumPy mean function works at a high level and it will also show you some of the details. So, you’ll learn about the syntax of np.mean, including … Read more
The NumPy linspace function (sometimes called np.linspace) is a tool in Python for creating numeric sequences. It’s somewhat similar to the NumPy arange function, in that it creates sequences of evenly spaced numbers structured as a NumPy array. There are some differences though. Moreover, some people find the linspace function to be a little tricky … Read more
Recently, a Sharp Sight blog reader emailed me and asked for advice about data science prerequisites. He was nervous about math. Someone had told him that in order to study data science, he needed to learn a long list of math topics first: Precalculus Calculus Multi variable calculus Trigonometry Linear algebra Differential equations Statistics Although … Read more