Businesses have started to invest in software and services that use machine learning and artificial intelligence (AI) across all industries to increase efficiency and acquire a competitive edge. — By: Gurleen Kaur Introduction MLOps is a strategy for integrating machine learning applications into enterprise production environments so that business and IT operations can benefit with a quicker integration. MLOps work by creating a framework of best practises and centralised management when mapped to an organization’s business model and objectives for developing business intelligence…

In this article, we are going to learn how to build a hybrid recommendation system — By: Daksh Bhatnagar INTRODUCTION A recommender system, or a recommendation system (sometimes replacing ‘system’ with a synonym such as a platform or an engine), is a subclass of information filtering systems that provide suggestions for items that are most relevant to a particular user. …

A Summary of the historically important events that conventionalized and materialized the God in a box that we know as ChatGPT. By: Gurleen Kaur Chatbots Chatbots are software applications that simulate human conversation. They follow a set of pre-designed rules to mimic real-life interactions and answer customer questions. …

Understanding the Mathematics Behind Gradient Descent Regression and Developing a NumPy-Only Implementation for the Algorithm — By: Gurleen Kaur Basic Linear Regression A variable’s value can be predicted using linear regression analysis based on the value of another variable. The dependent variable is the one you want to predict. The independent variable is the one you’re using to make a prediction about the value of the other variable.

In this article, we would discuss some feature selection techniques that you can use to select the features that will be fed to the Machine Learning model of your choice — By: Daksh Bhatnagar INTRODUCTION In the data science community, it is usually said that your predictions are as good as your data which means if your data has been pre-processed correctly and in a thoughtful manner, 9 times out of 10 you are likely to get the results you are looking for. …

In this article, we are going contrast the two-dimensionality reduction techniques that are Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA) — By: Daksh Bhatnagar Introduction As time went on, the size of the data has grown substantially. Businesses nowadays want to consider each and every aspect before making a decision which translates to higher dimensionality in real-life data.

In this article, we are going to take a look at how to scrape data from web using BeautifulSoup and Selenium and clean the data for further analysis. — By: Daksh Bhatnagar INTRODUCTION Extracting data from sources these days is really important since data is mostly stored in databases, a hosted web page, or can only be accessed via an API. For scraping data from the database, we generally use SQL (Structured Query Language), (HELLO, ARTICLE IDEA FOR THE FUTURE!!) however for data…

In this article, we will take a look at some of the ways to make a Jupyter Notebook look more appealing. — By Daksh Bhatnagar INTRODUCTION Which one do you like better? Below are two images. Take a look at both of them and evaluate them for a moment to decide which one is more appealing to look at.

Learning how XGBoost became such a popular model in today’s time in the data science community. — By Daksh Bhatnagar Introduction First of all, let’s understand what XGBoost means. XGBoost or Extreme Gradient Boosting is an upgrade of Gradient Boosting where the model simply learns to predict the residuals or the errors of the previous decision tree. Sequential decision trees are trained to predict the errors and iteratively…