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Name: Gaurav Haramkar
Type: User
Bio: Data Scientist | Machine Learning | Deep Learning | Artificial Intelliegence Developing machine learning & deep learning models to solve bussiness problems.
Location: Pune India
Name: Gaurav Haramkar
Type: User
Bio: Data Scientist | Machine Learning | Deep Learning | Artificial Intelliegence Developing machine learning & deep learning models to solve bussiness problems.
Location: Pune India
This project demonstrates analytics of football results of international football matches starting from the very first official match in 1972 up to 2019. The matches range from FIFA World Cup to FIFI Wild Cup to regular friendly matches. In this project I have done an in-depth analysis of the football match results and performed EDA on the football results data to uncover lots of hidden insights related to football matches. Cluster analysis is performed to observe the year wise trend of matches won by different teams. Feature engineering is performed to generate meta-features for analyzing the different aspect of football results.
**FinMan Health Insurance Lead Prediction:-** Our client 'FinMan' is a financial services company that provides various financial services like loan, investment funds, insurance etc. to its customers. 'FinMan' wishes to cross-sell health insurance to the existing customers who may or may not hold insurance policies with the company. The company recommend health insurance to it's customers based on their profile once these customers land on the website. Customers might browse the recommended health insurance policy and consequently fill up a form to apply. When these customers fill-up the form, their Response towards the policy is considered positive and they are classified as a lead. Once these leads are acquired, the sales advisors approach them to convert and thus the company can sell proposed health insurance to these leads in a more efficient manner. **Problem :** The task is to build a model to predict whether the person will be interested in their proposed Health plan/policy. **Data Source :** Analytics Vidhya
Create, Send, Transform JSON Data
This project deals with home loan approval prediction based off various features. Binary classification is implemented here using various classification techniques and performance analysis is carried out for each approach.
Classify a genetic mutation based on the evidence from the text based clinical literature.
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