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所在平台: Coursera专项课程 |
课程主页: https://www.coursera.org/specializations/tensorflow-advanced-techniques
课程评论：没有评论
课程名称：TensorFlow: 高级技术 课程概述： 在本课程中，您将学习TensorFlow的高级功能，了解功能API的基础，构建非顺序模型类型、定制损失函数和层。课程涵盖了优化技术，包括如何使用GradientTape和Autograph，在不同处理器和芯片类型的多环境中优化训练。您还将实践目标检测、图像分割以及卷积的可视化解释。此外，您还会探索生成性深度学习，了解AI如何生成新内容，包括风格迁移、自动编码器、变分自编码器(VAE)和生成对抗网络(GAN)。 您将获得的技能包括： - 模型可解释性 - 自定义训练循环 - 自定义及非传统模型 - 生成性机器学习 - 目标检测 - 功能API - 自定义层 - 分布式策略 - 基本张量功能 该专业化适合具备TensorFlow基础知识的软件和机器学习工程师，旨在通过学习TensorFlow高级功能来扩展他们的知识和技能，以便构建强大的模型。 课程结构： 1. 理解功能API的基础，构建非顺序模型类型及定制损失函数。 2. 学习优化的原理及GradientTape和Autograph的用法，并在多种处理器和芯片中优化训练。 3. 实践对象检测、图像分割和卷积的可视化。 4. 探索生成性深度学习及AI内容创作的方式。 学习方式： - 100% 在线课程，自主学习，设置灵活的截止日期。 - 中级水平，需要基础微积分、线性代数、统计学以及Python、TF/Keras/PyTorch框架的经验。 - 预计完成时间为约5个月，每周建议学习7小时。 完成之后，您将获得可分享的证书。该课程适合希望将模型部署到实际应用中的学习者。
Course Link: https://www.coursera.org/learn/custom-models-layers-loss-functions-with-tensorflow
Name:Custom Models, Layers, and Loss Functions with TensorFlow
Description:Offered by DeepLearning.AI. In this course, you will: • Compare Functional and Sequential APIs, discover new models you can build with the ... Enroll for free.
Course Link: https://www.coursera.org/learn/custom-distributed-training-with-tensorflow
Name:Custom and Distributed Training with TensorFlow
Description:Offered by DeepLearning.AI. In this course, you will: • Learn about Tensor objects, the fundamental building blocks of TensorFlow, ... Enroll for free.
Course Link: https://www.coursera.org/learn/advanced-computer-vision-with-tensorflow
Name:Advanced Computer Vision with TensorFlow
Description:Offered by DeepLearning.AI. In this course, you will: a) Explore image classification, image segmentation, object localization, and object ... Enroll for free.
Course Link: https://www.coursera.org/learn/generative-deep-learning-with-tensorflow
Name:Generative Deep Learning with TensorFlow
Description:Offered by DeepLearning.AI. In this course, you will: a) Learn neural style transfer using transfer learning: extract the content of an ... Enroll for free.
What you will learn
Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers.
Learn optimization and how to use GradientTape & Autograph, optimize training in different environments with multiple processors and chip types.
Practice object detection, image segmentation, and visual interpretation of convolutions.
Explore generative deep learning, and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to GANs.
Skills you will gain
Model Interpretability
Custom Training Loops
Custom and Exotic Models
Generative Machine Learning
Object Detection
Functional API
Custom Layers
Custom and Exotic Models with Functional API
Custom Loss Functions
Distribution Strategies
Basic Tensor Functionality
GradientTape for Optimization
About this Specialization
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About TensorFlow
TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. TensorFlow is commonly used for machine learning applications such as voice recognition and detection, Google Translate, image recognition, and natural language processing.
About this Specialization
Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs.
About you
This Specialization is for software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models.
Looking for a place to start? Master foundational basics with the DeepLearning.AI TensorFlow Developer Professional Certificate.
Ready to deploy your models to the world? Learn how to go live with the TensorFlow: Data and Deployment Specialization.
Applied Learning Project
In this Specialization, you will gain practical knowledge of and hands-on training in advanced TensorFlow techniques such as style transfer, object detection, and generative machine learning.
Course 1:
Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers.
Course 2:
Learn how optimization works and how to use GradientTape and Autograph. Optimize training in different environments with multiple processors and chip types.
Course 3:
Practice object detection, image segmentation, and visual interpretation of convolutions.
Course 4:
Explore generative deep learning and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to Generative Adversarial Networks.
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Intermediate Level
Intermediate Level
Basic calculus, linear algebra, stats
Knowledge of AI, deep learning
Experience with Python, TF/Keras/PyTorch framework, decorator, context manager
Hours to complete
Approximately 5 months to complete
Suggested pace of 7 hours/week
Available languages
English
Subtitles: English
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Intermediate Level
Intermediate Level
Basic calculus, linear algebra, stats
Knowledge of AI, deep learning
Experience with Python, TF/Keras/PyTorch framework, decorator, context manager
Hours to complete
Approximately 5 months to complete
Suggested pace of 7 hours/week
Available languages
English
Subtitles: English
