Given weather, location, testing, and spraying data, this competition asks you to predict when and where different species of mosquitoes will test positive for West Nile virus. A more accurate method of predicting outbreaks of West Nile virus in mosquitoes will help the City of Chicago and CPHD more efficiently and allocate resources towards preventing transmission of this potentially deadly virus.

The telecom industry is faced by a common challenge of network congestions due to various factors. To solve this problem, we will use data usage information of mobile phones from various telecom companies and find out a relation between the features of the mobile phone service provider (eg => bytes consumed through various services, etc.) and types of network congestion.

Predict the probability that a customer will default on their premium payment, so that the insurance agent can proactively reach out to the policy holder to follow-up for the payment of premium

Being able to make accurate predictions of future revenue can be hugely important for businesses. This project will focus on forecast the next monthly revenue of a french chamapagne brand, which will inform the decision-making process across all areas of the business, from purchasing decisions and marketing activity to staffing levels.

Predict the department-wide sales for each store for the following year and model the effects of mark-downs on holiday weeks. Based on your findings, provide recommended actions, with prioritization placed on largest business impact.

The capstone project is a focused approach to attempt a real-life challenge with the learnings from the program. In this project, you will use a combination of various datasets and models to forecast and predict daily cases and deaths. You will also create various plots to gain insights and showcase your results. the data has been collected from different sources like WHO, WorldoMeters, 1Point3Arces and many more to understand various aspects and build relevant features to use in models.

Identify potential loan customers for a bank using classification techniques and compare models to select the best performing one.

Online E-commerce websites like Amazon use different recommendation models to provide different suggestions to different users. Amazon currently uses item-to-item collaborative filtering, which scales to massive data sets and produces high-quality recommendations in real-time. In this project, you will use similar concepts to create your own product recommendation system.

Examine the linkage between CEO compensation and company performance using the tools of descriptive and inferential statistics.

Predict and apply masks over the faces detected in images using Convoluted Neural Networks and image recognition algorithms. The goal of the project is to build a system that acts as a face detector to locate the position of a face in an image and apply a segmentation mask on the face. For this, we will utilise data from over 409 images and 1000 faces from the WIDER FACE dataset.

Create interactive dashboards using Tableau’s data visualization tools to provide policy-level insights to the CEO of an insurance company.

Past studies in Sarcasm Detection mostly make use of Twitter datasets collected using hashtag based supervision, but such datasets are noisy in terms of labels and language. Furthermore, many tweets are replies to other tweets and detecting sarcasm in these requires the availability of contextual tweets. In this hands-on project, the goal is to build a model to detect whether a sentence is sarcastic or not, using Bidirectional LSTMs. The dataset is collected from two news websites, theonion.com and huffingtonpost.com.