Blog | scisoftdev

Graph neural networks. Quickstart.

Posted on 30.04.2024 | by scisoftdev

A brief overview of sources of knowledge about graph neural networks

For a quick start in graph neural networks, I recommend that you familiarize yourself with the Stanford University course CS224W. Teacher Yuri Leskovets explains in detail and simply the processes of graph processing in machine learning on graphs, and also considers training graph neural networks. In addition to the video on YouTube, there are links to course materials that are located on the university website. Stanford CS224W: Machine Learning with Graphs and link to course materials on the university website.

Saving neural network weights to csv file (AML part 6)

Posted on 19.02.2021 | by scisoftdev

Saving the neural network weights to a csv file is much easier. In my opinion this option is faster and csv tables are easily exported to other databases. Another reason is the great versatility of this approach, since to save to the database, you need to raise the local server, while for the files you just need to allocate a directory.

Saving neural network weights to MySQL database (AML part 5)

Posted on 05.02.2021 | by scisoftdev

I’ve tested two options for saving and loading weights. The first option works with a MySQL database, the second saves to a CSV file.

Creating database for neural network (AML part 4)

Posted on 19.01.2021 | by scisoftdev

Exist huge number of database management systems (DBMS). Of course, there are graph databases as well. However, for ease of understanding, I settled on MySQL. There are two reasons for this. The first is that I have experience with this DBMS. Secondly, this is a large amount of previously written program code for working with MySQL that I can use in this project.

Thinking out loud (AML part 3)

Posted on 16.01.2021 | by scisoftdev

It is not difficult to maintain the weights. However, there are many factors to consider. For example, maybe need information about which neural network the weights belong to. To do this, necessary to record metadata of the neural network, such as the number of layers, the number of neurons in each layer, what exactly does the neural network do, what is the activation function of the network?

Reverse engineering (AML part 2)

Posted on 13.01.2021 | by scisoftdev

To better understand how the neural network from the book works, reverse engineering is needed. For example, understand how an image library converts an image into a digital set and sends them to the input layer of a neural network?

Neural network class (AML part 1)

Posted on 02.01.2021 | by scisoftdev

A neural network is a complex data classifier. Special libraries are used to transfer data, such as sound or image, to the neural network. These libraries provide a digital representation of the object. Weights in the network are represented by numbers from 1 * 10^-16 to 0.9.