Previously, we wrote blogs on many machine learning algorithms as well as many other topics to help you broaden your knowledge. Please kindly visit our site and we would be glad if we got some feedback from you to improve our writing. To see some of them, you can follow the mentioned links. Linear Regression […]
Statistics
How to calculate integration using Monte Carlo Method?
Introduction In mathematics, an integral assigns numbers to functions in a way that describes displacement, area, volume, and other concepts that arise by combining infinitesimal data. The process of finding integrals is called integration source. To solve the many Data Science problem we should use integration. In Data Science we need to use not only […]
How Can We Generate Random Number From Congruential Method?
What is Random Number A random number is one that is selected at random, as the name suggests, from a group of numbers. As they tend to be excessively slow for most applications in statistics and cryptography, the first methods for producing random numbers, such as dice, coin flipping, and roulette wheels, are still employed […]
Kruskal Wallis H Test in News Data
Kruskal Wallis H Test What is Kruskal Wallis H Test Kruskal Wallis H test is a kind of non parametric test which means that there is no presence of parameter and parent population from which sample has been taken is not normally distributed. Kruskal Wallis H test is also known as non parametric version of […]
Beyond and Within EDA: Taking EDA into Modelling
Beyond and Within EDA Introduction This blog is the continuation of the previous blog post A General Way of Doing EDA. Please follow that before reading this blog. Once we got the knowledge of the data like its properties and features, we can move ahead by taking that knowledge to make some sort of inference. […]
A General Way to Perform an EDA
EDA: Introduction Hello everyone, welcome back to another new blog where we will explore different ideas and concept one could perform while performing an EDA. In simple words, this blog is a simple walk-through of an average EDA process which might include (in top down order): Data Loading: From various sources (remote, local) and various […]
Python for Stock Market Analysis: Alpaca API
Introduction Alpaca Trading API is an API using which we can retrieve stock data in realtime. It provides various APIs and even streaming services. Please read about it in their docs. What is most exciting about this API and the librariy is that it returns the data as a Pandas Dataframe or even simple Dict […]
Introduction to Probability for Data Science: Getting Started
Introduction Hello there welcome to the new blog series about Probability in the Data Science field. Here in this blog, we will start from basic concepts needed in using Probability in some datasets. This blog is going to be very short and basic yet informative. Probability is all about measurement of some event’s occurrence. We […]
Python for Stock Market Analysis: Getting Started into Modeling Timeseries
Introduction Hello there, this is the part 5 of Python for Stock Market Analysis and in this part, we will continue from where we left i.e. modeling a timeseries. Finding a best set of parameters that gives highly accurate prediction is always a hard job and there is not always a guarantee that one can […]
Python for Stock Market Analysis: Getting Started into Timeseries Analysis
Introduction This is the part 4 of our Python for Stock Market Analysis series and here, we will be getting started with timeseries analysis. This part will not be exploring any prediction techniques yet as we will explore fundamental concepts in timeseries. Making Things Ready Here, we will import Pandas for data analysis, install as […]