Advanced Machine Learning - CS5824/ECE5424

Fall 2020

Instructor

Hoda Eldardiry

Description

This course will cover machine learning science, including foundations, analysis, and applications of machine learning methods.

Learning objectives

A student who completes this class should (1) have a better understanding of machine learning, and (2) be able to leverage machine learning to solve real-world problems. In particular:

Understanding of ML

• Familiarity with a breadth of foundational machine learning concepts.
• Awareness of the mathematical and computer science concepts underlying machine learning.
• Acquiring background knowledge to be able to understand new machine learning methods not covered in the course.

Application of ML

• Ability to formulate real-world problems into machine learning tasks.
• Ability to make informed decisions about which machine learning methods are appropriate for different tasks.
• Ability to implement standard machine learning methods without using prepackaged machine learning software.

Topics

Supervised learning, unsupervised learning, and best practices in machine learning.

Prerequisites

Experience in Python, data structures, algorithms, calculus, linear algebra, probability, and statistics.

Projects

• Credit Card Fraud Detection Using Machine Learning
• Drowsiness Detection System
• Stock Market Prediction with LSTM Neural Networks
• Autonomous-Tagging-Of-Stack-Overflow
• SUPER-SPREADING MODELING AND PREDICTION
• Analysis of Bikeshare Availability in Metro D.C.
• DETECTING MISINFORMATIVE CONTENTS THROUGH USERS COMMENTS AND REVIEWS
• Dust Particle Recognition using microscopic images
• MOTION PREDICTION FOR AUTONOMOUS VEHICLES
• Text Classification of OSHA accident report using Machine Learning
• Macro and Micro Economic Regime Detection
• Analyzing the Accuracy of Face Recognition Model with Occlusions
• Attacking Federated Learning with Data Poisoning
• Financial Analysis
• CT Image Analysis of Natural Rocks with Deep Neural Network
• Reinforcement Learning for Autonomous Vehicles
• 4G and 5G Wireless Signal Classification With Machine Learning
• Comprehensive Assessment of Neural Network Synthetic Training Methods using Domain Randomization for Orbital and Space-based Applications
• Analyzing Models for Depth Map Prediction from Monocular Images
• Analyzing and Improving Models for Interactive Machine Learning
• Analyzing Athletic Performance and Readiness via HRV
• Prediction of Wind Generated Ocean Waves
• Spiking Neural Networks for Image Classification
• Drug synergy prediction using machine learning based model
• Alzheimer Disease Detection
• Emotional Detection From Audio with Neural Nets
• FPGA Routing Congestion Estimation using Machine Learning
• FANTASY PREMIER LEAGUE TEAM PREDICTOR
• Sentiment Analysis on COVID-19 Twitter Data
• Analyze the Algorithm of soccer match movement identification
• Machine Learning Based Detection of Cyber Attacks on PMU Measurements