Deep Learning | NYU Data Science Center Course

New York University

Dive into the latest advancements in deep learning with this hands-on course from NYU's renowned Data Science Center. Explore cutting-edge techniques in computer vision and natural language processing.

University CoursesLuaMachine Learning

Introduction

This increasingly popular course is taught through the Data Science Center at NYU. Originally introduced by Yann Lecun, it is now led by Zaid Harchaoui, although Prof. Lecun is rumored to still stop by from time to time. It covers the theory, technique, and tricks that are used to achieve very high accuracy for machine learning tasks in computer vision and natural language processing. The assignments are in Lua and hosted on Kaggle.

Highlights

Covers the theory, techniques, and tricks of deep learning
Taught by renowned experts in the field, including Yann Lecun
Hands-on assignments using Lua and Kaggle

Recommendation

This course is highly recommended for anyone interested in the latest advancements in deep learning and its applications in computer vision and natural language processing. It provides a solid foundation in the theory and practical implementation of deep learning models.

GetVM 是如何工作的？

从浏览器侧边栏中学习

从浏览器侧边栏中访问

从浏览器侧边栏中访问

简单安装浏览器扩展并点击侧边栏中启动 GetVM。

选择你的环境

选择你的环境

从我们的环境库中选择你的操作系统、IDE 或应用，并立即启动。

边学边做

边学边做

在教程或视频的侧边栏中，在 VM 中实践你的新技能。保存你的工作，以便在将来继续学习。

探索相似的教程

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.

A Selective Overview of Deep Learning 3

Technical TutorialsDeep LearningMachine LearningNeural Networks

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

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.