kishorejayshankar Goto Github PK

credit-card-fraud-detection-with-machine-learning

This project aims to detect fraudulent credit card transactions using machine learning techniques. The goal is to identify potential fraudulent activities so that customers are not charged for unauthorized purchases.

customer-churn-data-analysis-using-power-bi

This repository contains the code and resources for a customer churn data analysis project conducted entirely using Power BI. The project aims to analyze customer churn data, derive insights, and provide recommendations for improving customer retention strategies.

customer-segmentation-data-analysis-using-power-bi-and-sql

Customer segmentation is a crucial aspect of marketing strategy as it helps businesses understand their customers better and tailor their marketing efforts accordingly. By dividing customers into groups based on similarities such as demographics, behavior, or purchasing patterns, businesses can target each segment more effectively.

customer-sentiment-data-analysis-using-python-and-power-bi

This project focuses on analyzing customer sentiment through the implementation of the NLTK (Natural Language Toolkit) algorithm on product web reviews. The process involves extracting data from a SQL database, applying sentiment analysis using Python, generating CSV files, and then visualizing the data in Power BI for deeper insights.

datascientist

flipkart-reviews-sentiment-analysis-using-python

This project aims to predict whether a review given on Flipkart is positive or negative using machine learning techniques. By analyzing user reviews and ratings, we can gain insights into product quality and provide recommendations for improvement.

kishorejayshankar.github.io

langchain

🦜🔗 Build context-aware reasoning applications

personalized-product-recommendation

Recommending the right T-shirts to each customer can be challenging with a vast selection. Traditional recommendation systems may struggle to capture the nuances of individual preferences, leading to suboptimal suggestions and missed opportunities for sales.

quantium-data-analysis-internship

It involves analyzing chip purchases at supermarkets, aimed at evaluating customer purchasing behaviors and the performance of trial stores with a new layout.

recommendation-system-with-machine-learning-using-python

This project implements a movie recommendation system with Machine Learning using Python. The recommendation system utilizes collaborative filtering and content-based filtering techniques to provide personalized movie recommendations based on user preferences and movie attributes.