I have recently moved from a data analyst role to a data scientist role. This might not sound like a big change to you, but in reality these two roles can be quite different.
Disclaimer: This is my experience and it might be very different from yours! I just want to share my personal experience here with those of you who want to make this transition and don’t know where to start.
What is the difference between data science and data analytics?
Depends on the company!
Different companies use the title of data scientist in different ways. For example, a…
This is the second post from my series on A/B testing. In part 1, we learned the idea behind an A/B test. In this post, I walk you through the statistics behind A/B testing and focus more on analyzing the results of the test. I will use the final project of Udacity’s A/B testing course as a case study.
We will go over:
Udacity, which is an online learning platform, has two options on its course overview page start free trial and access course materials.
If students click on…
A/B testing is a hard concept to understand and explain. In this post I will walk you through the theory behind A/B testing.
Our focus will be the following topics:
A/B testing is a method that is used to test performance of the launch of a new feature or a change in an existing feature on online platforms. This methodology is often called hypothesis testing and is used in many different fields. For example, in medicine, researchers run clinical trials and use hypothesis testing…
In this series of blog posts, I’d like to explain how to use machine learning algorithms to solve specific problems in the data science world. Here, in the very first post, I walk you through the definition of machine learning (or simply ML) and different types of learning algorithms.
According to Andrew Ng, there is no single definition for machine learning. Arthur Samuel, a pioneer in AI, defined machine learning as the field of study that enables a computer to learn without being explicitly learned.
Tom Mitchell in his Machine Leaning book, gives a little bit of colour and clarity…
Imagine that we have two versions of a website, A and B. The only difference between these two versions is the design of the “sign-up” button. The question that we ultimately want to answer is that which version has higher conversion rate (users who sign-up/users who view the sign-up button).
We don’t go through the details of A/B testing analysis in this post. Instead, I’d walk you through a very short introduction of Bayesian A/B testing.
To understand the Bayesian statistics better, we need to know about some famous mathematical distributions.
Binomial distribution is a discrete probability distribution of the…
As a data analyst, I use Pandas package on a daily basis. It enables me to answer many questions about the data I’m working with. In this post, we are going through some of these questions and we’ll see how methods and functions in Pandas can help us to answer them.
I use the Iris dataset in this post. The Iris dataset, consists of three species of Iris, Iris setosa, Iris virginica, and Iris versicolor. For each species, the length and the width of sepal and petal in centimeter were measured.
You can either load the dataset through a .CSV…