Hi folks, I work as a Data Scientist at Bharti AXA General Insurance and while interviewing candidates for Data Science position, the foremost thing I analyse is-candidate’s knowledge on the Basic Data Science Algorithms.One should know the basic Data Science Algorithms in depth before moving to the advanced Algorithms. Today’s…

This is my first blog post of my Blogging Series “Brushing Up Linear Algebra” Most of us try to learn Mathematics and its applications but end up just learning the numerical computations.Mathematics is more than numerical computations.The Magic of Mathematics begins when we understand the geometrical interpretations of the numerical…

Hi folks,Thanks a lot for reading my blog posts and motivating me for writing.You can read all my blogs Here. This is an introductory blog on Time Series Analysis. We come across many instances in real life where we try to forecast what will happen in future(tomorrow,next week,next month,next year…

The core purpose for insurance has remained same over the years but new dimensions and innovations are transforming the Insurance industry.Unlike traditional insurance where assets are insured,Parametric Insurance insures parameters also known as indices. Parametric insurance comes in role when a specific event occurs or a measurable condition is met…

Hi All!! In this blogpost lets try to Appreciate Numpy and add one more reason to why Python is a fabulous language. In this blogpost we would try to understand three important questions Why should we use Numpy? What is Numpy? How do we use Numpy Why should we use Numpy? Python has incredibly large…

Hi Learners!! Today lets try to unlock Bayes’s Theorem. This blog will cover : 1.Probability 2.Conditional Probability 3.Conjoint Probability 4.Bayes’s Theorem 5.Applications of Bayes’s Theorem Probability : Probability is a number between 0 and 1,including both 0,1 where : The value 1 indicates the certainty that an event will occur.The value 0…

If you would have read my earlier blogs,I have covered two most popular classification algorithms Linear Discriminant Analysis and K-Nearest Neighbors. Another very popular Supervised Classification algorithm is Naive Bayes. Before diving deep lets understand What does Naive and Bayes signify. This algorithm is called “Naive” because it makes a…

K-Nearest Neighbors is one of the most basic algorithm used for Classification. KNN is a non parametric algorithm (meaning, it does not make any underlying assumptions about the distribution of data)belonging to supervised learning community. KNN algorithm can also be used for regression problems.The …

Linear Discriminant Analysis(LDA) is a very common technique used for supervised classification problems.Lets understand together what is LDA and how does it work. What is Linear Discriminant Analysis ? Linear Discriminant Analysis is a dimensionality reduction technique used as a preprocessing step in Machine Learning and pattern classification applications. The main goal of dimensionality reduction techinques…