SDE-2: Tech@Kotak || Ex Lowe's - Omnichannel Platforms

github

Rishindra Mani Katiyar  • Peerlist

A Conversational solution that enables customers to discover and order products. It helps in bridging the gap between online and offline experiences and enhances overall shopping experience. A host of integrations are provided to make the shopping experience hassle free and convenient for customer to order and discover products.

AI Conversational Shopping And  Human Plus Bot Hybrid Suppor

We try to find some interesting insights in movies released between 1916 and 2016. For this we use IMDb movie dataset and generate meaningful insights from the various fields using Python.

Application: Jupyter Notebook
Language: Python

Analysis of Movie Dataset

FIFA 19’s dateset gives detailed description of all the players that are participating in FIFA 19 tournament. The dataset contains information of all 18207 players from the latest edition FIFA 19. There are 89 attributes including like age, name, nationality, ball control, dribbling, crossing, finishing, GK skills, etc.
An attempt is made to bring out interesting insights from the dataset. An interactive dashboard is used to make data visualization more intuitive and drill deeper into various attributes of the dataset.

Data Visualization Tool: Tableau

FIFA 19: Data Analysis and Visualization

Bay Wheels (previously known as Ford GoBike) is a regional public bike sharing system in the San Francisco Bay Area, California. An attempt is made to conduct an exploratory data analysis on the dataset for FY2018 to get a deeper insight into bike riding patterns of the customers.
https://github.com/rishindramani/Udacity-Nanodegree-Projects/tree/master/Ford%20GoBike%20Trip%20Data%20Interpretation

Ford GoBike Trip Data Interpretation

Lending loans to ‘risky’ applicants is the largest source of financial loss (called credit loss) for lending companies. In this case study, we try to figure out driving factors (or driver variables) behind loan default. The company can then utilize this knowledge for its portfolio and risk assessment.

Language: Python

Gramener Case-Study

 An Image Recognition in Python in which kids are shown various images for some particular time duration and then they have to recognize them through their names. There are three levels in the game and the game progresses according to their performance in each level.

Language: Python

Kids Learning Game

The main objective of the Project is to manage the details of Inventory, Stocks, Sales and Medicines. The project is totally built at an administrative end and thus only the administrator is guaranteed the root access. 

Language: C++

Medicine Record Management System

Two of India's biggest stock exchanges BSE and NSE, collectively clear trades combining to greater than 40,000 crores every day. The dataset provided was extracted from the NSE website. The Stock price data provided was from 1-Jan-2015 to 31-July-2018 for six stocks: Eicher Motors, Hero, Bajaj Auto, TVS Motors, Infosys and TCS. We had to analyze closing price of the stocks using the Moving Average Method and generate corresponding signal as buy, sell or hold for the current stock.

RDBMS: MySQL

Stock Market Analysis

The pharmaceutical company Sun Pharma is manufacturing a new batch of painkiller drugs, which are due for testing. Around 80,000 new products are created and need to be tested for their time of effect (which is measured as the time taken for the drug to completely cure the pain), as well as the quality assurance (which tells you whether the drug was able to do a satisfactory job or not).

Domain: Inferential Statistics and Hypothesis Testing.

Sun Pharma Case Study

The aim of analysis is to identify the root cause of the problem (i.e. cancellation and non-availability of cabs) and recommend ways to improve the situation. The gap between supply and demand was illustrated visually which helped in crafting solutions to increase revenue during the peak hours.

Language: Python
Data Visualization Tool: Tableau 