A few years back, when I started my journey in data science, I was fascinated by Kaggle. I used to devote my time there. I was overwhelmed by the knowledge and problems. I wanted to be competitive and kaggle shows their leaderboard. You win and make a name. I used to have casual discussions with …
Why Problem Solving is the most important skill in Data Science? Read More »
Hi Guys!How have you been doing? Sorry for not writing anything in past few years. I had been doing crazy shit work. Ohh no.. that is just an excuse, I am telling myself. The motivation of restarting the blog came because I am seeing a lot of junk content on the web about data science(last …
Using GPU for deep learning has seen a tremendous performance. It has been reported that execution time using GPU is 10x -50x times faster than CPU-based deep learning and It is also a lot cheaper than CPU-based system. You can see this below in the picture. I was curious to check deep learning performance on …
Hi, future data science buddies! I have been asked many times how can I become data scientist or what should I do to become a data scientist. Here I have written about some technical skills that are required to be a data scientist. How to make career into Data Science But above article was lacking …
A Data Science Project-Introduction: How can we have better life expectancy! Read More »
Neural networks have been the most promising field of research for quite some time. Recently they have picked up more pace. In earlier days of neural networks, it could only implement single hidden layers and still we have seen better results. Deep learning methods are becoming exponentially more important due to their demonstrated success …
What is an Outlier? Simply speaking, Outlier is an observation that appears far away and diverges from an overall pattern in a sample. Let’s take an example, we do customer profiling and find out that the average annual income of customers is $0.8 million. But, there are two customers having annual income of $4 and $4.2 …
A brief introduction to Outliers and Outlier Removal methods Read More »
Have you ever given a thought how e-commerce websites show you products with “Customer who bought this also bought this” or how Netflix recommends movies based on your interest or how facebook discovers “Person you may know” list? Let’s look at the below pictures: Amazon: “When you buy a book” Netflix: “Other Movies You Might …
Lasso regression analysis is a shrinkage and variable selection method for linear regression models. The goal of lasso regression is to obtain the subset of predictors that minimizes prediction error for a quantitative response variable. The lasso does this by imposing a constraint on the model parameters that causes regression coefficients for some variables to …
People often get stuck when they are asked to improve the performance of predictive models. What usually they do is try different algorithms and check their results. But often they end up not improving the model. Today I will walk you through what we can do to improve our models. You can build a predictive …
As wikipedia defines: “Machine learning is a subfield of computer science[1] that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.[1] Machine learning explores the study and construction of algorithms that can learn from and make predictions on data.[2] Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions,[3]:2 rather than following strictly static program instructions.” i.e. you collect a …
Difference between Usual Machine Learning and Deep Learning Explained! Read More »