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所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-guide-to-tensorflow-for-deep-learning-with-python/
课程评论：没有评论
Coursera 课程总结：TensorFlow 深度学习 Python 完全指南 本课程旨在提供一个易于理解的 TensorFlow 框架指南，帮助学习者掌握使用 Google 的 TensorFlow 框架创建深度学习人工神经网络的技能。与许多其他课程不同，本课程侧重于纯 TensorFlow 的应用，让用户拥有更多控制权，并介绍最新的深度学习技术。 课程内容兼顾理论与实践，提供完整的 Jupyter Notebook 代码指南、易于参考的幻灯片和笔记，并包含大量练习以巩固所学知识。 **课程涵盖的主要主题包括：** * 神经网络基础 * TensorFlow 基础 * 人工神经网络 * 全连接网络 * 卷积神经网络 * 循环神经网络 * 自动编码器 * 强化学习 * OpenAI Gym **为何选择 TensorFlow？** TensorFlow 是一个开源的数值计算软件库，使用数据流图。图中的节点代表数学运算，边代表传输其中的多维数据数组（张量）。其灵活的架构支持单一 API 部署计算到桌面、服务器或移动设备上的一个或多个 CPU 或 GPU。 TensorFlow 最初由 Google Brain 团队开发，用于机器学习和深度神经网络研究，但其通用性使其适用于广泛的领域。Airbnb、Ebay、Dropbox、Snapchat、Twitter、Uber、SAP、Qualcomm、IBM、Intel 和 Google 等众多知名公司都在使用 TensorFlow。 加入本课程，成为机器学习专家！
Welcome to the Complete Guide to TensorFlow for Deep Learning with Python! This course will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand. Other courses and tutorials have tended to stay away from pure tensorflow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning! This course is designed to balance theory and practical implementation, with complete jupyter notebook guides of code and easy to reference slides and notes. We also have plenty of exercises to test your new skills along the way! This course covers a variety of topics, including Neural Network BasicsTensorFlow BasicsArtificial Neural NetworksDensely Connected NetworksConvolutional Neural NetworksRecurrent Neural NetworksAutoEncodersReinforcement LearningOpenAI Gymand much more! There are many Deep Learning Frameworks out there, so why use TensorFlow? TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google! Become a machine learning guru today! We'll see you inside the course!
