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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/intro-tensorflow
课程评论：没有评论
课程名称：Google Cloud上的TensorFlow 课程概述： 本课程涵盖了设计和构建TensorFlow 2.x输入数据管道、使用TensorFlow 2.x和Keras构建机器学习模型、提高机器学习模型的准确性、为大规模使用编写机器学习模型以及编写专门的机器学习模型。 课程大纲： 1. **课程简介** - 本模块提供了课程的概述及其目标。 2. **TensorFlow生态系统介绍** - 本模块介绍了TensorFlow框架，并预览其主要组件和整体API层次结构。 3. **设计和构建输入数据管道** - 数据是机器学习模型中的关键组件，仅仅收集数据是不够的。需要确保有合适的流程来清理、分析和转换数据，以便模型能够尽可能多地提取信号。本模块讨论了使用tf.data对大型数据集进行训练，处理内存文件，以及如何准备数据以进行训练，最后讨论嵌入及如何使用tf.keras预处理层进行数据扩展。 4. **使用TensorFlow和Keras API构建神经网络** - 本模块讨论了激活函数如何帮助深度神经网络捕捉数据的非线性特性，并提供有关使用Keras顺序和函数API的深度神经网络概述。接下来描述了模型子类化，提供了更大的模型构建灵活性。本模块最后提供了正则化的相关课程。 5. **使用Vertex AI进行大规模训练** - 本模块描述了如何使用Vertex AI对TensorFlow模型进行大规模训练。 6. **总结** - 本模块总结了在Google Cloud上使用Keras构建、训练和部署机器学习模型的课程内容。
Name:Introduction to the Course
Description:This module provides an overview of the course and its objectives.
Name:Introduction to the TensorFlow Ecosystem
Description:This module introduces the TensorFlow framework and previews its main components as well as the overall API hierarchy.
Name:Design and Build an Input Data Pipeline
Description:Data is the a crucial component of a machine learning model. Collecting the right data is not enough. You also need to make sure you put the right processes in place to clean, analyze and transform the data, as needed, so that the model can take the most signal of it as possible. In this module we discuss training on large datasets with tf.data, working with in-memory files, and how to get the data ready for training. Then we discuss embeddings, and end with an overview of scaling data with tf.keras preprocessing layers.
Name:Building Neural Networks with the TensorFlow and Keras API
Description:In this module, we discuss activation functions and how they are needed to allow deep neural networks to capture nonlinearities of the data. We then provide an overview of Deep Neural Networks using the Keras Sequential and Functional APIs. Next we describe model subclassing, which offers greater flexibility in model building. The module ends with a lesson on regularization.
Name:Training at Scale with Vertex AI
Description:In this module, we describe how to train TensorFlow models at scale using Vertex AI.
Name:Summary
Description:This module is a summary of the Build, Train, and Deploy ML Models with Keras on Google Cloud course.
This course covers designing and building a TensorFlow 2.x input data pipeline, building ML models with TensorFlow 2.x and Keras, improving the accuracy of ML models, writing ML models for scaled use and writing specialized ML models.
