from machine learning to deep learning. topics that i will cover (subject to some minor adjustment)...
TRANSCRIPT
![Page 1: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/1.jpg)
From Machine Learning to Deep Learning
![Page 2: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/2.jpg)
Topics that I will Cover(subject to some minor adjustment)
Week 2: Introduction to Deep LearningWeek 3: Logistic RegressionWeek 4: Multi-Layer Perceptron and Back PropagationWeek 5: Deep Learning (1) Week 6: Deep Learning (2)
![Page 3: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/3.jpg)
Week 2: Introduction to Deep Learning
• Deep learning can be viewed as a recent break-through in computer science
• In this lecture, I will introduce you a wide range of applications of Deep Learning techniques
![Page 4: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/4.jpg)
Week 3: Logistic Regression
• In order to understand Deep Learning, we need to first understand Artificial Neural Network
• We will start with a simple Artificial Neural Network: Logistic Regression
• We will talk about applying Logistic Regression to classification problems, and derive a learning algorithm that is called Iteratively Reweighted Least Squares (IRLS) for Logistic Regression
![Page 5: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/5.jpg)
Week 4: Multi-Layer Perceptron and Back Propagation
• In this lecture, we will develop a multi-layer perceptron based on Logistic Regression and introduce the back propagation algorithm for training multi-layer perceptrons
![Page 6: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/6.jpg)
Week 5: Deep Learning (1)
• In this lecture, we will talk about the issues of applying back-propagation algorithm to neural network with deep architectures
• Then will talk about unsupervised approaches for learning the weights for a deep neural networks layer by layer, which leads to different deep learning approaches
![Page 7: From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic](https://reader036.vdocuments.site/reader036/viewer/2022071807/56649ecf5503460f94bdd3b1/html5/thumbnails/7.jpg)
Week 6: Deep Learning (2)
• We will continue with week 5’s introduction on deep learning to further talk about the design, implementation, and applications of deep learning.
• I will talk about some of my own research work in this area, and suggest a couple of research directions that can work as Ph.D. dissertation topics.