Category: Machine Learning

This project is intended to be an introduction to Data Science and Machine Learning concepts as they are applied in the Cybersecurity domain. Beyond basic Python experience we don’t expect you to be familiar with these concepts so it will require you to spend time learning fundamentals of ML. This may require spending time watching…

This project is intended to be an introduction to Data Science and Machine Learning concepts as they are applied in the Cybersecurity domain. Beyond basic Python experience we don’t expect you to be familiar with these concepts so it will require you to spend time learning fundamentals of ML. This may require spending time watching…

This project is intended to be an introduction to Data Science and Machine Learning concepts as they are applied in the Cybersecurity domain. Beyond basic Python experience we don’t expect you to be familiar with these concepts so it will require you to spend time learning fundamentals of ML. This may require spending time watching…

Read carefully, section 4.3 Gradient-Based Optimization (pages 79 to 83) in “Goodfellow, I., Bengio, Y., Courville, A. (2016). Deep Learning. United Kingdom: MIT Press.” Then: Submit the algorithm in pseudocode (or any computer language) minimize vector x using gradient-based optimization: f(x) = 0.5 * ||A * x − b||^2, where A, x, and b are…

Use your own words to describe what machine learning is? (250 words.) Hint: You can explain supervised learning and/or unsupervised learning based on your own understanding. Or you can write a real-life example to explain the concept of machine learning.

Make sure all the code in the following notebooks are filled and running properly. Please return pdf back as a ipynb notebook.

this is my research topic Applying Unsupervised Machine Learning Algorithms to Detect Anomalies in Industrial Control Systems’ Network Traffic Data I need help with completing feature selection to use it in the Unsupervised learning algorithm. I’m using RapidMiner software for data analysis. Can you review my dataset version {HAIEnd 23.05} and perform feature selection, explaining…

In the context of Reinforcement Learning, Partially Observable Markov Decision Processes (POMDPs) extend MDPs to scenarios where the agent does not have full observability of the system state. This is particularly relevant in real-world applications where sensor noise, occlusions, or limited field of view prevent complete knowledge of the environment. Given a POMDP defined by…

Project Proposal: Implementation of a Network-Based Security Information System BY Your Name Reg N0: PROJECT REPORT SUBMITTED TO DEPARTMENT OF COMPUTER SCIENCE IN FULFILMENT OF REQUIREMENT FOR AWARD OF MASTER OF INFORMATION TECHNOLOGY (MIT); UNIVERSITY OF LAGOS, NIGERIA June, 2024 Supervisor: Dr. PROBLEM STATEMENT Background In today’s digital age, securing network infrastructure has become paramount.…

Define explainable AI based on the manuscript provided (150 words) Describe the impact of Explainable AI on two domains (150 words) Define the taxonomy of Explainable AI (150 words) Define one future application of Explainable AI and describe the potential impacts of this application (150 words).