Ashwin Tiwari

Data Scientist

Data Scientist

June 16, 2026 – Present

CV

October 24, 2023 – October 24, 2023

CV — GitHub repository

fuzzy

September 21, 2023 – September 21, 2023

fuzzy — GitHub repository

Neolen_assignment_task_cricket

December 10, 2020 – December 10, 2020

Predicting the winner of 2019 cricket world cup using random forest algorithm

Mahindra_First_choice

November 30, 2020 – November 30, 2020

Mahindra_First_choice — GitHub repository

boston-house-price-prediction

July 15, 2020 – March 20, 2021

boston-house-price-prediction — GitHub repository

Twitter_Sentiment_Analysis

July 12, 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.

credit_consumption_prediction_challenge

July 7, 2020 – July 7, 2020

Problem Statement Understanding the consumption pattern for credit cards at an individual consumer level is important for customer relationship management. This understanding allows banks to customize for consumers and make strategic marketing plans. Thus it is imperative to study the relationship between the characteristics of the consumers and their consumption patterns. Here the dataset is of some XYZ Bank that has given a sample of their customers, along with their details like age, gender and other demographics. Also shared are information on liabilities, assets and history of transactions with the bank for each customer. In addition to the above, data has been provided for a particular set of customers' credit card spend in the previous 3 months (April, May & June) and their expected average spend in the coming 3 months (July, August & September). The average spend for different set of customers needs to be predicted in the test set for the coming 3 months. Data Dictionary id Uni

Stayz-Rental-Prediction

May 3, 2020 – July 7, 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

customer-segmentation

March 2, 2020 – March 2, 2020

In this project we use sales data from an online retail store for customer segmentation.

ga-learner-dsmp-repo

September 26, 2019 – February 27, 2020

A collection of projects as part of the Data Science Masters Program at GreyAtom EduTech Pvt Ltd