Ravi Divecha

ShopAssist-GenAI-Bot

July 7, 2024 – July 7, 2024

Develop a chatbot that leverages a dataset comprising laptop information (including product names, specifications, descriptions, etc.) to deliver precise laptop recommendations tailored to user preferences

LlamaIndex-SemanticSearch

July 7, 2024 – July 7, 2024

To build a robust generative search using LlamaIndex capable of effectively and accurately answering questions from a list of policy documents. Our task is to build a proper Q/A bot using RAG, that the users can interact with and get answers from

IOT-Anomaly-Prediction

January 21, 2024 – January 21, 2024

IOT-Anomaly-Prediction — GitHub repository

WLC_Crash_Prediction

January 17, 2024 – January 17, 2024

Catalyst 9800-80 Wireless LAN Controller (WLC) experiences process crash events when operating at high scale

BeerRating-Ecommerce_Case-Study

January 9, 2019 – January 9, 2019

Build a recommendation system (collaborative), where customers will be recommended the beer that they are most likely to buy

SparkR-NewYorkCity-Parking-Case-Study

December 9, 2018 – December 9, 2018

Primarily, the case study is meant as a deep-dive into the usage of Spark. Compare the phenomenon related to parking tickets over three different years - 2015, 2016, 2017

Hive_NewYork_Cabs_Case_Study

November 26, 2018 – November 26, 2018

Case Study done in Hive for data of 2 months collected from NewYork City Cabs. The case study involved understanding the various aspects of any trip like no. of passengers, trip duration, tax amount and evaluation of how busy the days are for cab drivers.

Linear-Regression-Case-Study

November 5, 2018 – November 5, 2018

A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.

SVM-Hand-Writing-Case-Study

November 5, 2018 – November 5, 2018

A classic problem in the field of pattern recognition is that of handwritten digit recognition. Suppose that you have an image of a digit submitted by a user via a scanner, a tablet, or other digital devices. The goal is to develop a model that can correctly identify the digit (between 0-9) written in an image.

Gramener-Case-Study

November 4, 2018 – November 4, 2018

Company wants to understand the driving factors (or driver variables) behind loan default, i.e. the variables which are strong indicators of default. The company can utilize this knowledge for its portfolio and risk assessment. If one is able to identify these risky loan applicants, then such loans can be reduced thereby cutting down the amount of credit loss. Identification of such applicants using EDA is the aim of this case study