Difference between revisions of "AI: Anomaly Detection in logfiles"
Jump to navigation
Jump to search
(→Step 1) |
|||
| Line 17: | Line 17: | ||
First you need to create a sequential model, which can be trained later. | First you need to create a sequential model, which can be trained later. | ||
model = Sequential() | model = Sequential() | ||
Our model will use 1 input layer 1 hidden layer with 128 nodes and 1 output layer with a single node. | |||
WIP | WIP | ||
Revision as of 19:18, 12 July 2022
➤ IMPORTANT: This page is still under construction.
Summary
This guide will create a basic AI model to perform binary classification in order to detect anomalies in logfiles. This AI model is also suitable for the Jetson AGX Xavier Development Kit
Requirements
- Packages: TensorFlow, Keras, Pandas, sklearn, numpy, seaborn, matplotlib
- Software: Pycharm or any other python editor
Description
Step 1 - Create a model
First you need to create a sequential model, which can be trained later.
model = Sequential()
Our model will use 1 input layer 1 hidden layer with 128 nodes and 1 output layer with a single node.
WIP
Step 2
WIP
Used Hardware
Courses
WIP
References
WIP