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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-deep-learning-with-keras/
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课程名称：使用Tensorflow 2.x和Keras的实用深度学习 课程概述： 这门课程是针对深度学习初学者而设计的，内容更新到了Tensorflow 2，新增了关于实际转移学习的章节。TensorFlow是目前最受欢迎的深度学习库，受到Google的支持，是机器学习和人工智能领域的重要投资。许多人在入门Tensorflow时常常会陷入复杂的数学理论中，此课程旨在简化这一过程，帮助新手在没有繁重数学负担的情况下轻松学习。 课程特点： - 适合于机器学习新手和曾学习过但未能实际应用的学习者。 - 从基础开始，注重实践，快速进入编码阶段。 - 包含基本的理论知识，并通过代码解释几乎所有概念。 - 使用Keras和Tensorflow 2.x这两个强大而易用的机器学习工具。 课程内容： - 学习机器学习的基本模型。 - 高级模型的介绍，包括卷积神经网络、残差连接、Inception模块及Keras/Tensorflow 2.x的功能性API。 - 包含生物信息学领域的真实数据集，帮助学生理解如何将实际数据转化为机器学习模型的输入。 通过这门课程，学生将能够以极简的代码解决自己行业中的问题，所有示例都提供启动代码，帮助快速上手；同时，课程还包括视频运行示例的完整代码，方便学习者在遇到困难时参考。 课程提供快速的技术支持，所有问题将在24小时内回复。欢迎预约试听课程，以体验独特的教学风格和快速学习的方法。
**UPDATED: Now using Tensorflow 2. Please post in Q & A if you have any trouble. I'm here to help****UPDATED 11-2021: Added a section on Practical Transfer Learning**TensorFlow is by far, the most popular library for deep learning. Backed by Google, it is a solid investment of your time and efforts if you want to succeed in the area of machine learning and AI. The issue most people face is that getting started with Tensorflow guides usually delve too deeply into unnecessary mathematics. That is where this course comes in. While some theory is important, a lot of it is just not needed when you're just getting started! This course is for you if you are new to Machine Learning but want to learn it without all the complicated math. This course is also for you if you have had a machine learning course but could never figure out how to use it to solve your own problems. In this course, we will start from very scratch. This is a very applied course, so we will immediately start coding even without installation! You will see a brief bit of absolutely essential theory and then we will get into the environment setup and explain almost all concepts through code. You will be using Keras and Tensorflow 2.x - one of the easiest and most powerful machine learning tools out there. You will start with a basic model of how machines learn and then move on to higher models such as: Convolutional Neural Networks Residual Connections Inception ModuleFunctional API of Keras / Tensorflow 2.x Transfer Learning In this course, we explain concepts using not only toy datasets but also a real-world dataset from the bioinformatics domain. While you may not be interested in this particular domain, you would still learn a lot of important concepts that are involved in taking data from the real world and feeding it to ML models. This is the aspect of ML that is missing from almost all courses available on the internet today! Doing this would mean that you would be able to solve problems of your own industry after finishing this course. All with only a few lines of code. All the examples used in the course come with a starter code that will get you started and remove the grunt effort. The course also includes finished codes for the examples run in the videos so that you can see the end product should you ever get stuck. Do checkout the preview lectures on this page to get a better feel of the teaching style used in this course and how it can help you learn quickly. I provide unmatched support. All questions are answered within 24 hours. Try me and see. =]
