Training Neural Networks in Python (2022)

如果您不知道自己真正需要哪个工具、每种工具的用途以及它们的工作原理，那么拥有各种出色的工具供您使用是没有帮助的。在本课程中学习神经网络的内部工作原理，以便您能够更有效地使用机器学习工具。讲师 Eduardo Corpeño 通过提供一系列 Python 练习来帮助您通过示例学习，以帮助您掌握里面发生的事情。了解如何将生物神经元的各个部分与 Python 元素相关联，这使您可以制作大脑模型。然后，学习如何构建和训练网络，以及创建识别来自七段显示器的数字的神经网络。即使您可能会通过软件套件而不是编写自己的代码来使用神经网络，

本课程与 GitHub Codespaces 集成，这是一个即时云开发人员环境，无需任何本地机器设置即可提供您最喜欢的 IDE 的所有功能。借助 GitHub Codespaces，您可以随时在任何机器上进行实践练习——同时使用您可能会在工作场所遇到的工具。观看“在本课程中使用 GitHub 代码空间”视频，了解如何开始。

Released 11/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 2h 4m | Size: 496.7 MB

Having a variety of great tools at your disposal isn’t helpful if you don’t know which one you really need, what each tool is useful for, and how they all work. In this course learn the inner workings of neural networks, so that you’re able to work more effectively with machine learning tools. Instructor Eduardo Corpeño helps you learn by example by providing a series of exercises in Python to help you to grasp what’s going on inside. Discover how to relate parts of a biological neuron to Python elements, which allows you to make a model of the brain. Then, learn how to build and train a network, as well as create a neural network that recognizes numbers coming from a seven-segment display. Even though you’ll probably work with neural networks from a software suite rather than by writing your own code, the knowledge you’ll acquire in this course can help you choose the right neural network architecture and training method for each problem you face.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Check out the “Using GitHub Codespaces with this course” video to learn how to get started.