Data science is about putting theory into practice. Build up your hands-on skills in Statistics, Python, R, SQL, Tableau, Excel, Machine Learning, Deep Learning, and Time Series Analysis with our step-by-step, easy to understand tutorials and implement what you’ve learned in your future data science and analytics projects.
Tableau vs Excel is a hot discussion topic in the data science community. Indeed, Excel is not a top resume-building skill for aspiring data scientists. But it has been around for ages and you are probably familiar with tons of useful Excel tricks for data cleaning and analysis. Are you curious...
In our last tutorial, we looked into request headers and cookies and their role when you scrape data. So, what’s the next problem you could encounter when scraping? Yes, it’s login screens. Sometimes, you might set your sights on scraping data you can access only after you log...
There are two errors that often rear their head when you are learning about hypothesis testing – false positive and false negative, technically referred to as type I error and type II error respectively. At first, I was not a huge fan of the concepts, I couldn’t fathom how they could...
What is the ARIMAX model? If you've read our series of blog tutorials on models for estimating time series data, you're already familiar with 3 major approaches - autoregression, moving averages and integration. What's the common theme in all these models? They solely relied on a single...
If you’ve been researching or learning data science for a while, you must have stumbled upon linear algebra here and there. Linear algebra is an essential part of coding and thus: of data science and machine learning. But even then, you may be compelled to ask a question… Why is...
