From time to time, I keep coming across a lot of misinformation on Linear Regression. I hence created this meme to allay most of these misconceptions For Data Science Consulting and Solutions; Get in touch with us at: Website: https://www.arymalabs.com/ Linkedin: http://www.linkedin.com/in/venkat-raman-Analytics

“Do you think the model accuracy metrics are good enough? What should we do to improve the accuracy metrics ?”. The above question is very typical. You might have been asked this question at your work, Kaggle competitions or hackathons. This is a typical XY problem. …

First principles thinking is defined as “boiling problems down to their most fundamental truths”. So when it comes to Data Science, what are the first principles ? In my opinion they are : Measures of central tendency — Mean, Median, Mode. Measures of dispersion — Variance, Standard Deviation, Interquartile Range. …

Of late there is a greater impetus to ‘Automate Everything’ in Data Science. One such area is ‘Feature Selection’. I am of the firm opinion that ‘Feature Selection’ is best done by data scientist (with domain knowledge) and not through some automation. However, some don’t agree. I had been thinking…

The phrase “All models are wrong, some are useful” is quite loosely used. Some take it in a very literal sense to imply that “Modeling is a futile exercise”. This is a terrible misunderstanding and we shall see why shortly. “All models are wrong, some are useful” is an aphorism…

We often come across YouTube videos , posts, blogs and private courses wherein they say “We accept the Null Hypothesis” instead of saying “We fail to reject the Null hypothesis”. If you correct them, they would say what s the big difference? …

Abstraction — some succinct definitions. “Abstraction is the technique of hiding implementation by providing a layer over the functionality.” “Abstraction, as a process, denotes the extracting of the essential details about an item, or a group of items, while ignoring the inessential details” “Abstraction — Its main goal is to…

Every now and then, one stumbles upon on the statement “Logistic Regression is not regression, it is a classification algorithm” . On hearing this, many statisticians cringe (and rightfully so). Is Logistic Regression really a classification algorithm and not regression ? Absolutely not. Machine learning has usurped and renamed many…

I was recently invited to judge a Data Science competition. The students were given the ‘heart disease prediction’ dataset, perhaps an improvised version of the one available on Kaggle. …