surojitnath

BNP Paribas

Data Scientist

June 19, 2026 – Present

TextUtils_Django

December 22, 2020 – December 22, 2020

TextUtils_Django — GitHub repository

imageclassification

December 21, 2020 – December 21, 2020

imageclassification — GitHub repository

Dogcatclassification

December 13, 2020 – December 13, 2020

Dogcatclassification

Mahindra_First_choice

July 25, 2020 – July 25, 2020

Mahindra_First_choice — GitHub repository

house-price-prediction-boston

July 12, 2020 – March 20, 2021

house-price-prediction-Sinagpore using Flask and heroku

Twitter-Sentiment-Analysis

July 11, 2020 – July 12, 2020

Twitter has now become a useful way to build one's business as it helps in giving the brand a voice and a personality. The platform is also a quick, easy and inexpensive way to gain valuable insight from the desired audience. Identifying the sentiments about the product/brand can help the business take better actions. You have with you evaluated tweets about multiple brands. The evaluators(random audience) were asked if the tweet expressed positive, negative, or no emotion towards a product/brand and labelled accordingly.

HR-Analytics

May 11, 2020 – May 11, 2020

HR-Analytics — GitHub repository

Credit-Consumption-Prediction-Challenge

May 3, 2020 – May 3, 2020

Problem Statement Credit card consumption patterns are a gold mine for banks and financial companies. The consumption patterns and spends of a customer allow banks to build strategic partnerships with vendors for discounts or other plans to reward and retain customers. Further, banks can understand from the spending patterns and profile people based on spending and tailor the loans or financial products based on those. Thus it is important to understand the relationship between the customer profile and their spending patterns. The Common Man Bank Ltd (CMB) wants to understand these patterns thoroughly and get insights on the customer persona and the spending patterns. So from their database, they have prepared the data of sample customers and their transaction history. As a data scientist working with CMB, you are now supposed to mine insights from the data. CMB Bank has given customer details, like age, gender and other demographics. Also shared are information on liabilities, assets

Stayzee_Rental_Prediction

May 3, 2020 – May 3, 2020

Problem Statement : Stayze is an online market for providing lodging or primary homestays. The company does not own any real estate or properties, it acts as a broker receiving commission from each booking. The hosts rent out their property, its availability, area, type of room, price etc. and the travellers can book accordingly. The travellers put in their reviews, which is visible to others. People have used this service extensively and the company is recognized throughout the globe. All the online activities of the hosts as well as the travellers are being captured and have resulted in a rich database. This data can be used to gain business insights, make decisions, improve security, understand the customers' and providers' (hosts) behaviour and performance on the platform, guiding marketing initiatives, implementation of innovative additional services and much more. The stakeholders with the help of the available data want to know the ideal prices at which the properties can be ren

domain-classification-text

April 21, 2020 – April 21, 2020

Repo containing haptik chat data to classify topics using NLP