English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 48m | 496 MB
Learn about the purpose, structure, and training process of neural networks to improve your machine learning skills. In this project-based course, instructor Eduardo Corpeño teaches you how to create an intelligent system with a neural network from scratch in C++, as well as how to choose the right neural network architecture and training method for each problem. Eduardo starts by explaining the difference between a neural network and other programming tools. He goes over why this course uses C++ and how to add different types of neural networks to your toolbox. The inspiration for artificial neural networks is the brain, and Eduardo relates parts of a biological neuron to C++ elements, then shows how to use activation functions and perceptrons in building neuron models. Eduardo covers the steps you will need to build and train your network. He explains segment display recognition, then guides you through designing and training your own SDR neural network.
Table of Contents
Introduction
1 Create a neural network from scratch in C
2 What you should know
3 Using GitHub for the exercise files
Choosing a Neural Network
4 What is a neural network
5 Why C
6 The many applications of machine learning
7 Types of classifiers
8 Types of neural networks
9 Multilayer perceptrons
The Building Blocks of Neural Networks
10 Neurons and the brain
11 A simple model of a neuron
12 Activation functions
13 Perceptrons A better model of a neuron
14 Challenge Finish the perceptron
15 Solution Finish the perceptron
16 Logic gates
17 Challenge Logic gates with perceptrons
18 Solution Logic gates with perceptrons
Building Your Network
19 Linear separability
20 Writing the multilayer perceptron class
21 Challenge Finish the multilayer perceptron class
22 Solution Finish the multilayer perceptron class
Training Your Network
23 The need for training
24 The training process
25 Error function
26 Gradient descent
27 The delta rule
28 The backpropagation algorithm
29 Challenge Write your own backpropagation function
30 Solution Write your own backpropagation function
Make a Segment Display Classifier
31 Segment display recognition
32 Challenge Design your own SDR neural network
33 Solution Design your own SDR neural network
34 Challenge Train your own SDR neural network
35 Solution Train your own SDR neural network
Conclusion
36 Next steps
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