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Detecting log anomalies with machine learning

Linux and open source machine learning project. Github page: https://github.com/Dunttus/AI-Project

Author: Joni Hakala

Apache access.logs: example of good and bad log entries

Apache and PHP install for testing First we need to install Apachen and PHP module for users folder /public_html with … More

Access.log formatting, Apache log http status codes, Apache logs, Apache2, Apache2 php module, Log anomalies

PyCharm Pro Scientific Mode

NB! Scientific mode is only available in the Pro version of PyCharm. Started wondering how to execute Jupyter style of … More

# In[1]:, #%%, PyCharm, PyCharm Jupyter notebook, PyCharm Pro, Scientific Mode

Environment installation

Finished project installation guide on Github Web server anomaly detection Github page has full installation guide for manual and Docker … More

CUDA, cudNN, Docker, Docker install, Enviroment, Tensorflow Docker, Ubuntu 18.04.4LTS, Windows 10 Pro 1809

Where do we start?

After the project presentation, we will start by making a HelloWorld test prototype. The purpose of a prototype machine learning … More

HelloWorld, Log levels, Neural network example, Printk

Fetching data from ELK-Stack

NB! If you retrieve large amounts of information from ElasticSearch, the server may crash. Raw data At first, install Curl … More

.csv file from Kibana, Data from ELK-stack, Delete data from Elasticsearch, Elasticdump, Over 10.000 logs from ELK-stack, Raw data, Text processing

Project planning

Preliminary design ideas First, we designed the ideas on paper as text so that we could get some idea of … More

AI platform, Coding language, Planning, Purpose of project
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