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DSC 821 : Machine Learning
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Module 1: Introduction to Machine Learning & Applications
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Module Notes
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End of Module Quiz
Reflect on Your Journey
Module 2: Linear Regression
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Linear Regression Summary
Module 3: Support Vector Machines
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Support vector machines notes
Support vector machine example
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Module 4: Decision Trees, Random Forest and Boosting
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Milestone 1: Analyze Context and Situation
Interactive Learning Adventures
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Module 5: Neural Networks
Interactive Learning Adventures
Practical considerations when choosing neural network
Summary of Neural Networks
Single Layer Perceptron (SLP)
Deep Learning
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Module 6: Convolutional Neural Networks (CNNs)
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Convolutional Operations in CNNs notes
Convolutional Operations in CNNs notes continued
Convolution layer in a CNN Quiz
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End of Module Quiz
Convolutional Neural Network (CNN) notebook
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Neural Networks and Deep Learning
Module 7: Recurrent Neural Networks (Rnns) and Lstms
RNNs and LSTMs
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Module 8: Principal Component Analysis (PCA)
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Principal component analysis
PCA Implementation example
Integrating Dimensionality Reduction with Machine Learning Models
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MODULE 9: Reinforcement Learning
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Milestone 1: Analyze Context and Situation
Interactive Learning Adventures
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Module 10: Optimization in machine learning: Stochastic gradient descent
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Interactive Learning Adventures
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FINAL EXAMINATIONS
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Course info
DSC 821 : Machine Learning
Lecturer:
Group A
Course Duration in Hours
:
45
Skill Level
:
Beginner
Course rating
:
Course Objectives
: