By Kardi Teknomo, PhD. (If you have not read, check the FREE partial online edition here)

### Is it possible to perform Neural Network in Excel with only spreadsheet without macro programming? Yes, this tutorial will explain how to do it step by step.

We all heard the exaggeration of the media about neural network that neural network is a kind of intelligence system. If you have ever learned about neural network, I want to ask a few simple questions:

• How do you design a neural network that can do a simple subtraction like C = A-B?
• How do you design a neural network that can do a simple multiplication like C=A.B?
• How do you design a neural network that can do a simple division like C=A/B?
• How do you design a neural network that can do Boolean operation like ((A XOR B) AND C) OR (A AND B)?
• How do you design a neural network that can do a simple linear regression like y=m.x+c?
• How do you design a neural network that can do a simple forecasting for time series data?

If neural network is indeed an intelligent system, why to answer the above simple and obvious questions seems to be very difficult?

Most the books about neural network are too much sophisticated that they ignore the very basic lessons. Most of the authors assume the most readers understand higher mathematics and you must know calculus and how to program in C++ or Python. Is there any hope that you can do neural network in a simple scientific calculator or in spreadsheet without any programming? That is where this Neural Network tutorial coming in.  If you just want to grasp what is neural network, how does it works and how can it be applied to solve the problems in your life (not to do research to build a new kind of neural network, but to use neural network for your daily life), then this tutorial is for you.

This tutorial emphasizes on the numerical examples, spreadsheet solutions as comprehensive projects and how to apply neural network to solve the real world problems from data to forecasting. This tutorial includes some very basic and obvious questions that many other neural network books simply does not provide any clue or answer. This neural network tutorial is really for beginners, to fill the gap of knowledge in the mathematics and programming. After reading this tutorial, you will have more confidence on what you can do and what you cannot do with neural network. It is your self-confidence that is very valuable, goes beyond any price.

We will start with the basic simplest neuron model, and then we will develop it into more and more complex network architecture. Depending on the network architecture, the non-linear function inside the neuron and the learning methods and its purposes, different name of neural network models was developed. However, in this tutorial we will discuss the most famous feedforward network such as McCulloch and Pit, Perceptron, ADaptive LInear Neuron (ADALINE), Multi-Layer Perceptron (MLP), Many ADaptive LInear Neuron (MADALINE) and Back Propagation Network.

Through the work numerical examples, you will learn step by step how to use the existing neural network and then how to build your own neural network that can learn from examples using mere spreadsheet of Microsoft Excel, without macro programming. Indeed, this is unique tutorial is useful for people who want to learn neural network in a very fast way. The spreadsheets companion of this tutorial are available for download only for those who purchase the full version of this tutorial.

The author assumes the readers have no prior knowledge on data science or neural network. The mathematics level has been pulled down to a high school level or into the beginning of college level. There is no need to understand calculus deeply and there is no programming is necessary. However, the author also assumes the readers know how to write formulas and how to use spreadsheet in Microsoft Excel. This is not Excel tutorial for beginners. In fact, after learning this book, you will appreciate how to use the spreadsheet in more powerful ways.

More than 50 numerical examples and spreadsheet comprehensive solutions are provided in this tutorial. The examples are given in boxes to represent the steps you need to master before going further. Exercises at the end of each section are very useful to explore the variation of values.

This ebook is unique! You cannot find this information of doing Neural Network only using Spreadsheet without programming anywhere else!

### What is Neural Network?

Artificial Neural Network is a family of models that intended to mimic the neural cells in the brain. The unit processing element is a simple model called a neuron. Each neuron is basically a function that can receive many inputs and produces only one output. Combining many neurons into a network of neurons is what we called as Artificial Neural Network or simply Neural Network for short.

### Why do you need to download this e-book and its companion files NOW?

• Save your learning time. Your time is very valuable. It saves a lot of your time to do self study on this topic.
• Understanding this topic will enhance your study, your work, and your research. Eventually you can develop it further to get more money for your future.
• If you are a teacher, reading this tutorial will help your students to understand the obvious and apply neural network in their life.
• By purchasing the FULL tutorial, you will be able to read tutorial in a very nice PDF format without advertising. You can zoom in and out to see the formulas clearly. You can read in any computing device (phone, tablet, PC, laptop, Mac, iPad).
• The full tutorial also comes in e-book together with the companion files. The spreadsheet tutorial will give you an eye opener to this fascinating topic. It enhances your understanding. The complete tutorial will be your self-study guide to improve your learning process. You can read it off-line anywhere anytime even when you don’t have internet connection.

More than 120 pages of Neural Network tutorial including more than 50 examples, mostly complete numerical examples and Excel comprehensive solutions. This Neural Network Tutorial e-book you will learn the following fascinating topics in a very SHORT TIME (click the links to see the FREE sample pages online):

1. What is Neural Network?
1. Why Use Neural Network?
2. Limitation of Neural Network
3. Neural Network Terminologies and Notations
2. Model of a Neuron
1. Aggregation Function
2. Activation Function
3. Bias and Dummy Input
3. Boolean Logic using Single Layer Neural Network
4. Input-Output Diagram of Perceptron
5. Building Neural Network using Spreadsheet
6. Training Single Layer Neural Network
8. Single Layer Bipolar Neural Network
9. Multi-Layer Neural Network
10. Training Neural Network using Back Propagation
1. Problems with Back Propagation
11. Training Neural Network Using Excel Solver
12. Plug & Play Neural Network
1. Boolean Neural Network
2. Arithmetic Neural Network
13. Neural Network for Regression Analysis
1. Simple Linear Regression
2. Multiple Linear Regression
3. Logistic Regression
4. Polynomial Regression
14. Applications of Neural Network
1. Design of Neural Network
2. Training Neural Network
3. Neural Network Utilization
15. Classification Application: Prediction Beyond Expert System
16. Image Processing Application: Optical Number Recognition
17. Forecasting from Time Series Data
18. Summary: Integrated Approach to Neural Network

Price

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