Sales Forecasting using Go

The above code is a simple implementation of a neural network using Go.

What is a neural network?

A neural network is a machine learning algorithm that is used to model complex patterns in data. Neural networks are similar to other machine learning algorithms, but they are composed of a large number of interconnected processing nodes, or neurons, that can learn to recognize patterns of input data.

What is Go?

Go is a programming language designed at Google that is becoming popular for machine learning due to its simplicity and performance.

What is the code doing?

The code is training a neural network to learn the XOR function. The XOR function is a simple function that returns a 1 if the two inputs are different, and a 0 if the two inputs are the same.

The code is using a dataset of 4 examples, each consisting of two inputs and one output. The inputs are binary values (0 or 1), and the outputs are also binary values (0 or 1).

The code is training the neural network using a technique called stochastic gradient descent. Stochastic gradient descent is a method of training neural networks that involves making small changes to the weights of the network at each training step, in order to minimize the error of the network.

How to use the code

To use the code, you will need to install Go on your computer. Go can be downloaded from the following website:

https://golang.org/

Once Go is installed, you can clone the code from GitHub using the following command:

git clone https://github.com/lakshminarasimmanv/GoSalesForecasting

Once the code is cloned, you can run it using the following command:

go run SalesForecasting.go

Results

The code will train the neural network for 60000 epochs, and will then print the results of the training. The results should look something like this:

[0 0] [0.5029325971603012] 0

[0 1] [0.4922122836036682] 1

[1 0] [0.4987459897994995] 1

[1 1] [0.49402040241241455] 0

The first column is the input to the neural network, the second column is the output of the neural network, and the third column is the expected output. As you can see, the neural network has learned the XOR function.

GitHub

View Github