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CS315 Machine Learning
Ch1 - Basic Probability
CS315 - Machine Learning
Dimensionality Reduction
Data Engineering 414
Data Engineering 414
Gradient Ascent
Linear Regression
Data Engineering 424
Clique Trees
Data Engineering 424
Practical 3 - DE424
Practical 5 - DE424
Untitled
Environmental Engineering 442
Environmental Engineering 442
Handouts - Part 2 - Week 1
Infobase
Introduction
start
Untitled
Operations Research 415
Local Search
Markov Chains Introduction
N-Step Transition
Operations Research 415
Tabu Search
Optimisation 414
Broydens Method
Genetic Algorithms
Golden Section Search
Local Search
Method of Gradient Ascent
Method of Gradient Descent
Newton Multivariate Method
Newton Univariate Method
Newton Univariate Root Method
Optimisation 414
Particle swarm optimisation
Secant Method
Simulated Annealing
Tabu Search
Project Management 412
Part 1 - Philosophy and Concepts
1. What is project management?
2. Systems Approach
Part 2 - Systems Development and PLC
3. Project Life Cycle and Conception
4. Project & System Definition
5. Project Execution & closeout
Part 3 - Systems & Procedures for Planning and Control
6. Project Planning Fundamentals
6.8 Line of Balance
7. Schedule Planning and Networks
8. Advanced project network analysis & scheduling
9. Cost Estimating & Budgeting
Project Management 412
Skripsie
Audio Technique
Classifiers
DER
Detection Metrics
Ground Truth
Literature Review
Meetings
NeMo
Notes
Speech 101 Notes
Writing
Stats 318
Statistics 318 - Project Proposal
Stats 348
Part B
a) Intro to Time Series Analysis
Models for Stationary Time Series
Statistics 348
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CS315 Machine Learning
❯
CS315 - Machine Learning
CS315 - Machine Learning
Sep 21, 2025
1 min read
CS315 - Machine Learning
Course Material:
Ch1 - Basic Probability
Dimensionality Reduction
Graph View
Backlinks
Introduction