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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-projects-with-tensorflow-20/
课程评论：没有评论
课程名称：使用 TensorFlow 2.0 进行机器学习项目 课程概述：TensorFlow 是全球最广泛使用的机器学习和深度学习框架，而 TensorFlow 2.0 作为一个重要的里程碑，引入了诸多重大变化，使其更易学习和使用，包括“即时执行”（Eager Execution）。此版本将支持更多平台和语言，改善兼容性并移除已弃用的 API。本课程将通过构建真实世界的机器学习项目，指导学员提升机器学习技能。 每个部分将涵盖一个特定的机器学习项目，学员将学习如何利用 TensorFlow 2 将其实施到自己的系统中。在课程中，学员将通过 TensorFlow 2 库实施多种机器学习技术和算法。每个项目将对学员的技能进行考验，帮助他们理解并克服在真实场景中可能遇到的挑战，并提供一些提高效率的技巧和建议。课程期间，学员将学习 TensorFlow 2 的新特性，例如即时执行，并涵盖至少 3-4 个项目。同时，还将探讨强化学习和迁移学习等任务。 到课程结束时，学员将能熟练构建自己的机器学习系统，并能将这一宝贵技能添加到个人简历中。 关于讲师：Vlad Ionescu 是巴贝什-博利亚大学的讲师，持有机器学习博士学位，致力于不断研究和探索机器学习领域，应用技术包括 Python、Keras 和 TensorFlow。他的教学哲学是：“如果我不能让大多数人理解某件事情，我需要重新理解它，再试一次。”这一理念促使他在讲座和教程中尽力而为。Vlad 最初是一名中学计算机科学教师，随后在大学层面教授各种课程和教程，涵盖语言、技术和概念，例如 Python、Keras、机器学习、C#、Java、算法和数据结构。在中学及大学时期，他参加了多项计算机科学竞赛和奥林匹克竞赛，并积极参与一些在线评测网站，还在算法标签中获得了 StackOverflow 金徽章。
TensorFlow is the world's most widely adopted framework for Machine Learning and Deep Learning. TensorFlow 2.0 is a major milestone due to its inclusion of some major changes making TensorFlow easier to learn and use such as "Eager Execution". It will support more platforms and languages, improved compatibility and remove deprecated APIs.This course will guide you to upgrade your skills in Machine Learning by practically applying them by building real-world Machine Learning projects.Each section should cover a specific project on a Machine Learning task and you will learn how to implement it into your system using TensorFlow 2. You will implement various Machine Learning techniques and algorithms using the TensorFlow 2 library. Each project will put your skills to test, help you understand and overcome the challenges you can face in a real-world scenario and provide some tips and tricks to help you become more efficient. Throughout the course, you will cover the new features of TensorFlow 2 such as Eager Execution. You will cover at least 3-4 projects. You will also cover some tasks such as Reinforcement Learning and Transfer Learning.By the end of the course, you will be confident to build your own Machine Learning Systems with TensorFlow 2 and will be able to add this valuable skill to your CV.About the AuthorVlad Ionescu is a lecturer at Babes-Bolyai University. He has a PhD in machine learning, a field he is continuously researching and exploring every day with technologies such as Python, Keras, and TensorFlow.His philosophy is "If I can't explain something well enough for most people to understand it, I need to go back and understand it better myself before trying again". This philosophy helps him to give of his best in his lectures and tutorials.He started as a high school computer science teacher while he was doing his Masters over 5 years ago. Right now, he teaches various university-level courses and tutorials, covering languages, technologies, and concepts such as Python, Keras, machine learning, C#, Java, algorithms, and data structures.During his high school and college years, he participated in many computer science contests and Olympiads and was active on some online judge sites. He also owns a StackOverflow gold badge in the Algorithm tag.
