AI Patasala Artificial Intelligence(Full Stack Data Scientist) Course Projects by Students

Problem Statement

• With the advancements in technology, credit card fraudulent activities have become more prevalent
• Credit card fraud leads to the loss of billions of dollars for consumers and financial companies
• In 2020, US alone lost whopping $9.47 billion through illegal credit card transactions

Solution

The aim of this project is to build a model that is capable of detecting credit card fraudulent transactions.

• We will be developing a fraud detection model using Machine Learning
• This model can be built using different ML algorithms
• We will also plot the respective performance curves for the models
• We will learn how data can be analyzed and visualized to discern fraudulent transactions from other types of data

Problem Statement

The dark world hackers are using system vulnerabilities to lure into systems and steal valuable data

• Malware Prediction protects machines from damage before it happens
• Malware prediction is one of the important step in the security of the computer systems

Solution

The aim of this project is to predict the system malware at an early stage to avoid data loss and

• We will be developing a fraud detection model using Machine Learning
• This model can be built using different ML algorithms
• We will learn how to predict malicious behaviour using machine activity data

Problem Statement

• Targeting potential users based on their peculiar interests can help enterprises in achieving the desired results
• But how to analyze and segment users based on their interest? This is a critical challenge for enterprises

Solution

We can group customers into sections of individuals who share common characteristics. This approach is called Customer Segmentation

• Customer Segmentation is one the most important applications of unsupervised learning
• This technique can help enterprises in identifying several segments of customers
• Companies can easily identify and target their potential user base
• Customer segmentation helps in delivering personalize experiences to customers

Problem Statement

• More than 25% of the revenue for the enterprises in the E-Commerce industry is attributed to apparel & accessories.
• Categorizing these apparels has become a critical problem from just the images especially when the categories provided by the brands are inconsistent
• Similarly classification of objects or living beings from images posses a lot of difficulty
• This image classification problem has caught the eyes of several Deep Learning researchers.

Solution

The Image Classification problem is to categorize all the pixels of a digital image into one of the defined classes.

• This technique is most critical use case in Digital Image Analysis
• Image classification is an application of both supervised classification and unsupervised classification
• We will build the Image Classification Model that is capable of classifying objects in an image

Problem Statement

Apple launched Siri that offered a real-time, faster, and easier speech recognition system. The first speech recognition system, Audrey, was developed back in 1952. By 2011

• To make the system recognize a word spoken by the user
• To display the correctly recognized word on a character LCD
• When compared with humans, the speech recognition systems are lacking millennia of contextual experience
• Voice inputs divert too much especially with the changes in accents which is a major challenge for Speech to Text application

Solution

A Speech-to-Text API synchronous recognition request is the simplest method for performing recognition on speech audio data

• We will be developing a fraud detection model using Machine Learning
• We will use a real-world dataset and build this speech-to-text model
• This project will help you understand how the Python code works
• So get ready to use your Python skills