Machine Learning for Meal Delivery App
In this project, you will predict the demand for various meal items for a meal delivery app. This forecasting is important for the company to plan its inventory, especially perishables and level of staffing. You have a dataset that contains historical demand data and several attributes like meal type, price, geographical area, etc. You will also come up with a model to develop meal-type segments that will provide several insights to the marketing team on how to position these meal types in their promotions.
Working on this project will help you apply the various concepts of demand forecasting and segmentation on a real-life problem.
Predict the Popularity of a Mobile App
The smartphone revolution has led to the emergence of millions of mobile apps developed for varied applications. Amidst this competitive environment, an app must be popular and lead to a high number of downloads. In this project, you will predict how successful or popular a mobile app would be based on certain attributes of the app. You will come up with targeted recommendations for different categories of mobile apps based on their attributes. This is an interesting project that you can relate to several mobile apps that you use every day.
Detect the Age of Actors Using Computer Vision
In this project, you will use image analytics and computer vision to detect the age of actors based on their images extracted from a movie database. Working on this project will give you immense exposure to core deep learning concepts like Convolutional Neural Networks (CNN) and multi-class classification modelling. The dataset has several other attributes like pose, expression, etc., which provides scope to extrapolate your learnings to other aspects of image classification.
Extract Drug Side Effects Using Natural Language Processing
The pharma industry launches several new drugs that are meant for curing diseases, health and wellness and for symptomatic treatment. People use these drugs and provide their opinions on these drugs and their experiences while using these drugs. This is a gold mine of information that can reveal the benefits as well as the harmful side effects of these drugs. The challenge is that there a huge amount of data available. To overcome this challenge, you will use information retrieval, text mining, entity extraction and sentiment analysis to extract the most common benefits and harmful side effects of several drugs. With the increasing use of NLP in healthcare analytics, this project will be an attractive addition to your portfolio.