Top 10 Deep Learning Projects for Engineering Students in 2022

Chatbots

Due to their skillful handling of a profusion of customer queries and messages without any issue, Chatbots play a significant role for industries. They are designed to lessen the customer service workload by automating the hefty part of the process. Nonetheless, chatbots execute this by utilizing their promising methods supported by technologies like machine learning, artificial intelligence, and deep learning. Therefore, creating a chatbot for your final deep learning project will be a great idea.

Forest Fire Prediction

Creating a forest fire prediction system is one of the best deep learning projects and it will be another considerable utilization of the abilities provided by deep learning. Forest fire is an uncontrolled fire in a forest causing a hefty amount of damage to not only nature but the animal habitat, and human property as well. To control the chaotic nature of forest fires and even predict them, you can create a deep learning project utilizing k-means massing to comprehend major fire hotspots and their intensity.

Digit Recognition System

This project involves developing a digit recognition system that can classify digits based on the set tenets. The project aims to create a recognition system that can classify digits ranging from 0 to 9 using a combination of shallow network and deep neural network and by implementing logistic regression. Softmax Regression or Multinomial Logistic Regression is the ideal choice for this project. Since this technique is a generalization of logistic regression, it is apt for multi-class classification, assuming that all the classes are mutually exclusive.

Image Caption Generator Project in Python

This is one of the most interesting deep learning projects. It is easy for humans to describe what is in an image but for computers, an image is just a bunch of numbers that represent the color value of each pixel. This project utilizes deep learning methods where you implement a convolutional neural network (CNN) with a Recurrent Neural Network (LSTM) to build the image caption generator.

Traffic Signs Recognition

Traffic signs and rules are crucial that every driver must obey to prevent accidents. To follow the rule, one must first understand what the traffic sign looks like. In the Traffic signs recognition project, you will learn how a program can identify the type of traffic sign by taking an image as input. For a final-year engineering student, it is one of the best deep learning projects to try.

Credit Card Fraud Detection

With the increase in online transactions, credit card frauds have also increased. Banks are trying to handle this issue using deep learning techniques. In this deep learning project, you can use python to create a classification problem to detect credit card fraud by analyzing the previously available data. 

Customer Segmentation

This is one of the most popular deep learning projects every student should try. Before running any campaign companies create different groups of customers. Customer segmentation is a popular application of unsupervised learning. Using clustering, companies identify segments of customers to target the potential user base.

Movie Recommendation System

In this deep learning project, you have to utilize R to perform a movie recommendation through technologies like Machine Learning and Artificial Intelligence. A recommendation system sends out suggestions to users through a filtering process based on other users’ preferences and browsing history. If A and B like Home Alone and B likes Mean Girls, it can be suggested to A – they might like it too. This keeps customers engaged with the platform.

Visual tracking system

A visual tracking system is designed to track and locate moving object(s) in a given time frame via a camera. It is a handy tool that has numerous applications such as security and surveillance, medical imaging, augmented reality, traffic control, video editing and communication, and human-computer interaction.

Drowsiness detection system

The drowsiness of drivers is one of the main reasons behind road accidents. It is natural for drivers who drive long routes to doze off when behind the steering wheel. Even stress and lack of sleep can cause drivers to feel drowsy while driving. This project aims to prevent and reduce such accidents by creating a drowsiness detection agent.