This is the competition hosted by kaggle to predict the house price using regression techniques. The first part of the challenge was to understand the data using visualization techniques. Second part was cleaning, transforming and precoessing the data. The next part was feature extraction and engineeing procedded by model development and validation of the results.
(Competition hosted by analytics vidhya)
Problem Statement: Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customers segments, those are eligible for loan amount so that they can specifically target these customers.
(Competition hosted by analytics vidhya)
Forecasting the traffic on JetRail for 7 months using traffic data provided since the inception of JetRail.
(Competition by Analytics Vidhya) Given the tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc, the task is to identify if the tweets have a negative sentiment towards such companies or products.