Most Recognizable Big Data Projects

Chatbot Construction

Due to their ability to efficiently process a high volume of consumer messages and inquiries, chatbots play an essential role in modern organizations. They have automated many customer support procedures, significantly reducing our workload. Methods such as A.I., ML, and Data Science-backed are used.

Identifying Credit Card Fraud

Credit card fraud is more prevalent than you may imagine, and recent numbers have been especially high. Only in 2022 is it safe to assume that we will have exceeded the symbolic threshold of one billion credit card holders. However, credit card issuers have been able to detect and prevent these scams with significant accuracy because of developments in Artificial Intelligence, Machine Learning, and Data Science.

Spot the Fake: Identifying Unreliable Reporting

We don’t have to give an introduction to fake news. Today’s globalized society makes it laughably simple to spread misinformation online. Unauthorized sources occasionally disseminate false information online, which can have far-reaching consequences, including widespread alarm and even acts of violence.

This Data Science endeavor aims to detect the legitimacy of the content to reduce the spread of fake news. Moreover, python’s TfidfVectorizer and PassiveAggressiveClassifier are used to construct a model for distinguishing between authentic and fraudulent news. You can use News.csv as your data source using the Python tools pandas, NumPy, and scikit-learn.

Risk Assessment of Future Wildfires

One useful application of Data Science is developing a system for predicting forest and wildfires. Unpredictable flames ravaging a forest are what we mean when we talk about a wildfire. Forest wildfires have historically been responsible for much destruction, not just to the forest itself but to animal habitats and human property.

Identifying the Types of Breast Cancer

If you’re looking for a healthcare-related project to add to your portfolio, one option is to create a Python-based breast cancer detection system. Recent years have seen an uptick in breast cancer diagnoses, and the most effective strategy for combating this disease is to catch it early and begin treatment.

The IDC(Invasive Ductal Carcinoma) dataset comprises histology images of cancer-inducing malignant cells, making it ideal for training a Python-based system to detect cancer. Convolutional Neural Networks are the best choice for this assignment; for the Python libraries, you can use NumPy, OpenCV, TensorFlow, Keras, scikit-learn, and Matplotlib.

Detection of Driver Fatigue and Sleepiness

Many people lose their lives yearly due to traffic accidents, and drowsy driving is a common contributing factor. A sleepiness detection system is one of the finest ways to ensure that drivers are always alert.

Another project with the potential to save many lives of driver drowsiness detection systems is constantly monitoring the driver’s eyes and alarming him if they detect frequent closing of eyes.

A webcam is required for the system to check on the driver’s eyes periodically. Therefore, a deep learning model and packages like OpenCV, TensorFlow, Pygame, and Keras are needed for this Python task.