In Python, the = (assignment) operation does not pass by reference. Instead, it binds a new name to the same object. This behavior is more accurately described as creating a reference to the object. When dealing with mutable objects like lists, modifying the object through any reference will affect all…

Love grows. Like a fungus over a monsoon laden earth under the shadow of a dripping Banyan. It grows into something. A sense of care. A habit. Noise in the ears when she is around, and a dense emptiness when she is not. Not like the everlasting love of Radha…

apply() works on both DataFrames and Series, allowing custom functions for transformation. map() is specifically for Series objects and is useful for value replacement or mapping. applymap() is applied to all elements in a DataFrame and is handy for element-wise operations. apply() apply() is a Pandas DataFrame and Series method that…

The article discusses recommender systems, focusing on Collaborative Filtering and Content-Based Filtering methods. Collaborative Filtering uses user interaction data, while Content-Based Filtering relies on item characteristics for personalized recommendations. Hybrid systems combine both methods for better results. — Collaborative Filtering and Content-Based Filtering are two fundamental approaches used in recommender systems to provide personalized recommendations to users. These methods are designed to address the challenges of information overload and help users discover relevant content or products.

1. INTUITION Imagine you have a basket of colorful marbles, and you want to group them based on their colors. But there’s a twist. You don’t know how many different colors are in the basket, and some marbles might be a mix of two or more colors. This is where Gaussian Mixture…

1. INTUITION Imagine you have a field of stars in the night sky, and you want to group them based on how densely they are packed together rather than a predetermined number of clusters. This is where DBSCAN, which stands for Density-Based Spatial Clustering of Applications with Noise, shines like a cosmic…

This article uncovers the key components of recommender systems, algorithms, and considerations behind their effectiveness. — Suggested Pre-Read: Recommendation Systems: An Introduction Recommendation systems are powerful tools that cater to the dynamic needs of consumers. Shoppers seek highly…aaweg-i.medium.com A good recommender system is one that provides accurate and relevant recommendations to users,

In today’s fiercely competitive Consumer Packaged Goods (CPG) industry, success hinges on strategic advantage. This article explores the pivotal role of advanced CPG analytics and AI, shedding light on how these tools can empower CPG companies to drive growth, enhance efficiency, and deliver personalized experiences. Dive into the world of data-driven strategies that are reshaping the post-pandemic CPG landscape.

Recommendation systems are powerful tools that cater to the dynamic needs of consumers. Shoppers seek highly personalized experiences from the brands they engage with. This article explores the world of recommendation systems, delving into their functionality, advantages, real-world applications, and notable examples of companies that have harnessed their potential. What is a Recommendation System?