ECE657A

Lect 4B -

Lect 4B - Admin and Questions

Autoencoders

Autoencoders

Bite-Size Science: The

Bite-Size Science: The Art of Machine Learning with Kishansingh Rajput

Integrated Machine Learning

Integrated Machine Learning in Open-Ended Crane Scheduling:Learning Movement Speeds and Service Time

Decision Trees Pruning

Decision Trees Pruning and Implementations

Inception - Resnet

Inception - Resnet - Densenet

Week 2S 1.3

Week 2S 1.3 Hypothesis Testing

Introduction to Neural

Introduction to Neural Networks Concepts and History

Unsupervised Learning -

Unsupervised Learning - Clustering Definitions and Hierarchal Algorithms

Adding Time :

Adding Time : Recurrent Neural Networks

Parameter Estimation -

Parameter Estimation - Bias vs. Variance - Unbiased Estimators - Cross-validation

Lect 8B-1 Course

Lect 8B-1 Course Admin

Decision Tree Costs

Decision Tree Costs Evaluation

t-Stochastic Neighbor Embedding

t-Stochastic Neighbor Embedding (t-SNE)

Deep Learning by

Deep Learning by Gradient Descent

Lect 4A -

Lect 4A - Admin and Announcements

Support Vector Machines

Support Vector Machines

Convolutional Neural Networks

Convolutional Neural Networks II

Deep Learning -

Deep Learning - Fundamentals III (optional)

JSSPP2022: Encoding for

JSSPP2022: Encoding for Reinforcement Learning Driven Scheduling

Clustering - Density

Clustering - Density Based - DBScan

Classification - Introduction

Classification - Introduction

Lect 11B -

Lect 11B - Admin Intro

Week 2S Part

Week 2S Part 1 - ProbStatsReview -Conditional Prob and Bayes Theorem

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