When we solve a machine learning problem, the algorithm that we may end up using depends on the type of data that we have and the problem itself. And despite having numerous algorithms to choose from, there is still a general procedure or framework that we follow to solve our problem. — In this post we will go through that generic process or framework which can be used as a template to solve any machine learning problem. After reading this article, you will -

Have you ever played one of those finish-the-pattern games? There are 6 shapes of different colors given in a row and you have to guess what the 7th shape will be. It is fascinating that even though we have never seen those kinds of patterns before we are still able to guess it correctly (well most of the times…) — What is happening here is that we are performing pattern recognition entirely based on what we really see and that too without any given rules to direct or streamline our judgement. …

In an era of bootcamps and learn-xyz-in-7-days, books still remain to be the most valuable resource one can avail. Data Science is still gaining a lot of popularity and getting a lot of attention. Hence it is the perfect time for you to get into this field. — Disclaimer: As an Amazon Associate, I may earn a small commission for any endorsement, recommendation, testimonial, and/or link to any products or services I have mentioned below. Your purchase helps support my work in bringing you real information about Data Science.

Like humans can tell apart jam from jelly (or can we?), with the help of machine learning, now machines can also label and categorize objects that they see. But they must be trained for it. Let’s see what that means… — In this article, I want to go over a very important topic in Machine Learning — Supervised Learning. This is the most popular form of machine learning used in the industry. After reading this post:

Imagine that you are in a contest. The host presents you with three doors. Behind one of those doors is a brand new Audi and behind the other remaining two doors are goats. The host asks you to choose one of these three doors, and then proceeds to open one of the other two remaining doors to reveal a goat. Now tell me, do you stick to your initial door or do you switch to the other unopened door to get your Audi?

This post is to provide you with an end-to-end Data Science learning path — a journey that begins with Linear Algebra, going over to classical Artificial Intelligence all the way to advanced Machine Learning topics like Reinforcement Learning and Deploying Machine Learning models. This will be updated regularly. — Let me start by stating the reason why having such a learning path is necessary and why it will prove to be extremely valuable to you. As a Data Science professional, I get these questions on a daily basis: “How do I start learning Data Science?” “Where do I get the resources…

Even though there are numerous machine learning algorithms each with a different approach, there is a general procedure which is followed to solve any machine learning problem. In this article, we will understand how all of that happens. — If you would like to get a general introduction to Machine Learning before this, check out this article: So what is Machine Learning? I am sure by now you must have heard about this term, and if surprisingly not, just have a look at the presentations by…thedatascienceportal.com

This list was last updated in 2020 — and will be updated regularly so as to keep it relevant — There are a lot of great online resources and websites on data science and machine learning that one can leverage in order to learn something new or maybe work on an existing skill now. …

“Data Scientist — The sexiest job of the 21st Century “ I am sure you have heard this even if you are not a data-head like I am. This was in a major publication from Harvard Business Review by Thomas H. Davenport and DJ Patil where they talked about how…