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Learning Deep Learning: Unit 3

Learning Deep Learning: Unit 3

本课程是 Learning Deep Learning 专项课程的一部分

位教师：Pearson

包含在中

了解更多

1个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

1个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master large language models and transformer architectures for advanced natural language processing applications.
Build and deploy multimodal networks that integrate multiple data types, such as text and images.
Implement multitask learning and solve advanced computer vision problems, including object detection and segmentation.
Apply ethical principles and practical strategies for tuning and deploying deep learning models in real-world settings.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

5 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Learning Deep Learning 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有1个模块

This course covers key deep learning architectures such as BERT and GPT, focusing on their use in applications like chatbots and prompt tuning. You will learn how to build models that combine text and images, and generate text from visual data. The course also addresses multitask learning and computer vision tasks, including object detection and segmentation, using networks like R-CNN, U-Net, and Mask R-CNN. Topics include ethical considerations in AI and practical advice for tuning and deploying models. Through hands-on projects in TensorFlow and PyTorch, you will develop the skills needed to build, optimize, and apply deep learning solutions in real-world situations.

This module explores advanced deep learning topics, including large language models (LLMs) and their transformer architectures, multimodal networks that integrate multiple data types, and multitask learning for complex computer vision tasks like object detection and segmentation. Practical implementation is demonstrated using TensorFlow and PyTorch. The module concludes with guidance on ethical considerations, model tuning, and further learning directions, equipping learners to responsibly apply deep learning in real-world scenarios.

涵盖的内容

33个视频5个作业

33个视频总计239分钟

Topics 1分钟
Overview of BERT 10分钟
Overview of GPT 7分钟
From GPT to GPT4 17分钟
Handling Chat History 6分钟
Prompt Tuning 9分钟
Retrieving Data and Using Tools 8分钟
Open Datasets and Models 6分钟
Demo: Large Language Model Prompting 6分钟
Lesson 8 Summary 2分钟
Topics 1分钟
Multimodal learning 8分钟
Programming Example: Multimodal Classification with TensorFlow 8分钟
Programming Example: Multimodal Classification with PyTorch 8分钟
Image Captioning with Attention 6分钟
Programming Example: Image Captioning with TensorFlow 18分钟
Programming Example: Image Captioning with PyTorch 17分钟
Multimodal Large Language Models 20分钟
Lesson 9 Summary 2分钟
Topics 1分钟
Multitask Learning 6分钟
Programming Example: Multitask Learning with TensorFlow 5分钟
Programming Example: Multitask Learning with PyTorch 6分钟
Object Detection with R-CNN 7分钟
Improved Object Detection with Fast and Faster R-CNN 5分钟
Segmentation with Deconvolution Network and U-Net 8分钟
Instance Segmentation with Mask R-CNN 3分钟
Lesson 10 Summary 2分钟
Topics 1分钟
Ethical AI and Data Ethics 19分钟
Process for Tuning a Network 6分钟
Further Studies 5分钟
Learning Deep Learning: Summary 8分钟

5个作业总计150分钟

Large Language Models Quiz 30分钟
Multi-Modal Networks and Image Captioning Quiz 30分钟
Multi-Task Learning and Computer Vision Beyond Classification Quiz 30分钟
Applying Deep Learning Quiz 30分钟
End of Course Assessment 30分钟

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Pearson

268 门课程 47,305 名学生

提供方

Pearson

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无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

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常见问题

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.