“Whispers of Literary Impulse” — An Anthology
An Checklist of Guidelines for the Anthology planned in January 2024 | Last updated: 4th August, 2023. — UPDATE: Please check the current list of entries selected for the Anthology here: Whispers of Literary Impulse The poems selected for the Anthology till Datemedium.com Dear Writers and Creatives, We hope this letter finds you in high spirits and brimming with creativity. You, as writers, hold the power to inspire, provoke, and transport readers to realms of imagination. Literary Impulse aims to…
MEDITATIONS — A Collection
“Meditations” is about a journey into the depths of the human experience. It is a colllection of essays, memoirs, reflections and philosophic prose. Each essay evokes a sense of contemplation and offers a glimpse into the beauty and complexity of life. — What does ‘Failure’ Mean in the Age of Artificial Intelligence Transcending Anger: Embracing Harmony and Love In the Realm of Poetic Existence Inside the Womb of Slowness
Poetry Reviews Archive | Literary Impulse
Critical Analysis of Captivating Poems — Welcome to the Poetry Reviews Archive, a repository of the articles I have published, dedicated to exploring the captivating world of poetry. Within these virtual pages, you will find a collection of insightful and thought-provoking reviews that delve into the rich tapestry of poetic expressions, uncovering the depths of emotions…
Python: apply(), map(), and applymap() for Data Manipulation
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…
Recommender Systems: Collaborative Filtering and Content-Based Filtering
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.
Introduction to Gaussian Mixture Models (GMM) with Expectation-Maximization (EM)
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. …
Recommender Systems: What goes into making one? — A Checklist
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,
AI Strategy for Consumer Packaged Goods (CPG) with focus on Recommender Systems
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.