本课程适合所有想通过动手编程学习神经网络如何工作的人！
每个人都在谈论神经网络，但如果不自己建立一个，它们很难理解。幸运的是，所需的数学和编程技能 (python) 处于基础水平，因此我们可以在 3 个多小时内对 3 个神经网络进行编程。不要浪费你的时间！本课程经过优化，可让您在尽可能短的时间内深入了解这个迷人的主题。
重点完全放在边做边学上，我只在需要时才引入新概念。
你会学到什么
简短介绍后，课程分为三个部分 – 每部分 1 小时
1) 搭建最简单的神经网络：计算两个数之和。
您将了解
神经网络架构
权重、输入和输出层
训练和测试数据
精度和误差函数
前馈和反向传播
梯度下降
2）我们修改这个网络：确定和的符号。
您将被介绍给
隐藏层
激活功能
分类
3）我们的网络可以应用于各种问题，比如图像识别：确定手写数字！
看完这个酷炫又好用的现实生活应用，我给你一个展望
如何改善网络
神经网络还能解决哪些其他问题？
如何轻松使用预训练网络
为什么是我？
我的名字是 Börge Göbel，我是一名博士后，在理论物理学领域工作，神经网络被广泛使用。
作为理论物理学学士、硕士和博士生的导师，我提高了顾问技能，并在 Udemy 上开设了其他成功的课程。
Published 06/2022
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.36 GB | Duration: 29 lectures • 3h 32m
From intuitive examples to image recognition in 3 hours – Experience neuromorphic computing & machine learning hands-on
What you’ll learn
Program neural networks for 3 different problems from scratch in plain Python
Start simple: Understand input layer, output layer, weights, error function, accuracy, training & testing at an intuitive example
Complicate the problem: Introduce hidden layers & activation functions for building more useful networks
Real-life application: Use this network for image recognition
Requirements
Basic programing skills are desired if you want to program along with me. We use Python3 without any advanced modules.
Description
This course is for everyone who wants to learn how neural networks work by hands-on programming!
Everybody is talking about neural networks but they are hard to understand without setting one up yourself. Luckily, the mathematics and programming skills (python) required are on a basic level so we can progam 3 neural networks in just over 3 hours. Do not waste your time! This course is optimized to give you the deepest insight into this fascinating topic in the shortest amount of time possible.
The focus is fully on learning-by-doing and I only introduce new concepts once they are needed.
What you will learn
After a short introduction, the course is separated into three segments – 1 hour each
1) Set-up the most simple neural network: Calculate the sum of two numbers.
You will learn about
Neural network architecture
Weights, input & output layer
Training & test data
Accuracy & error function
Feed-forward & back-propagation
Gradient descent
2) We modify this network: Determine the sign of the sum.
You will be introduced to
Hidden layers
Activation function
Categorization
3) Our network can be applied to all sorts of problems, like image recognition: Determine hand-written digits!
After this cool and useful real-life application, I will give you an outlook
How to improve the network
What other problems can be solved with neural networks?
How to use pre-trained networks without much effort
Why me?
My name is Börge Göbel and I am a postdoc working as a scientist in theoretical physics where neural networks are used a lot.
I have refined my advisor skills as a tutor of Bachelor, Master and PhD students in theoretical physics and have other successful courses here on Udemy.
I hope you are excited and I kindly welcome you to our course!
Who this course is for
This beginner-friendly course is for everyone! Especially if you
Are curious about neural networks and want to really understand how they operate
Work in machine learning or data science but have not yet programed a neural network yourself from scratch
Want to really learn about machine learning without fancy frameworks/modules – Just you, me & standard python
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