A Selective Overview of Deep Learning

Fan, Ma, Zhong

Comprehensive overview of key concepts and recent advancements in deep learning, covering neural network models, training techniques, and theoretical foundations.

Technical TutorialsDeep LearningMachine LearningNeural Networks

Introduction

A Selective Overview of Deep Learning by Fan, Ma, Zhong provides a statistical and scientific perspective on the key concepts and recent advances in deep learning. It introduces common neural network models and training techniques, highlights the new characteristics of deep learning, and discusses the theoretical foundations of this powerful machine learning approach.

screenshot

Highlights

  • Covers common neural network models such as convolutional neural networks, recurrent neural networks, and generative adversarial networks
  • Explains training techniques like stochastic gradient descent, dropout, and batch normalization
  • Highlights the new characteristics of deep learning, including depth and over-parametrization, and their practical and theoretical benefits
  • Samples recent results on the theories of deep learning, providing insights into this rapidly evolving field

Recommendation

This course is recommended for anyone interested in understanding the statistical and scientific foundations of deep learning. It provides a comprehensive overview of the key concepts and recent advancements, making it valuable for both beginners and experienced practitioners in the field of machine learning and artificial intelligence.

How GetVM Works

Learn by Doing from Your Browser Sidebar

Access from Browser Sidebar

Access from Browser Sidebar

Simply install the browser extension and click to launch GetVM directly from your sidebar.

Select Your Playground

Select Your Playground

Choose your OS, IDE, or app from our playground library and launch it instantly.

Learn and Practice Side-by-Side

Learn and Practice Side-by-Side

Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.

Explore Similar Hands-on Tutorials

Getting Started with Artificial Intelligence , 2nd Edition

25
Technical TutorialsData ScienceMachine Learning
Comprehensive introduction to AI, covering machine learning and data science. Practical guide to building enterprise applications with real-world examples.

Machine Learning For Dummies, IBM Limited Edition

19
Technical TutorialsData ScienceMachine Learning
Comprehensive guide to machine learning and data science, suitable for beginners and experienced professionals. Authored by experts Daniel Kirsch and Judith Hurwitz.

Data Mining Concepts and Techniques

25
Technical TutorialsData ScienceMachine Learning
Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis.

A Brief Introduction to Machine Learning for Engineers

29
Technical TutorialsMachine Learning
Gain a solid understanding of machine learning concepts and techniques for engineers. Covers supervised, unsupervised, probabilistic models, and advanced topics.

A Comprehensive Guide to Machine Learning

24
Technical TutorialsData ScienceMachine Learning
Detailed resource on machine learning, data science, and artificial intelligence. Authored by experienced experts, suitable for beginners and experienced learners.

A First Encounter with Machine Learning

2
Technical TutorialsData ScienceMachine Learning
Explore fundamental machine learning concepts, algorithms, and applications in data science. Suitable for beginners interested in learning about this rapidly growing field.

Algorithms for Reinforcement Learning

6
Technical TutorialsMachine LearningReinforcement Learning
Comprehensive guide to reinforcement learning algorithms, covering dynamic programming, temporal difference, Monte-Carlo methods, and more. Suitable for researchers, students, and practitioners in AI, ML, and control engineering.

Approaching Almost Any Machine Learning Problem

8
Technical TutorialsMachine LearningPython
Comprehensive guide to problem-solving approaches in machine learning, suitable for beginners and experienced practitioners. Covers a wide range of ML topics and techniques.

Deep Learning for Coders with Fastai and PyTorch

17
Technical TutorialsMachine LearningPyTorch
Comprehensive introduction to deep learning using the fastai library and PyTorch, suitable for beginners and experienced coders.