AnushaUpadhyaya / Intrusion Detection System
I have tried some of the machine learning and deep learning algorithm for IDS 2017 dataset. The link for the dataset is here: http://www.unb.ca/cic/datasets/ids-2017.html. By keeping Monday as the training set and rest of the csv files as testing set, I tried one class SVM and deep CNN model to check how it works. Here the Monday dataset contains only normal data and rest of the days contains both normal and attacked data. Also, from the same university (UNB) for the Tor and Non Tor dataset, I tried K-means clustering and Stacked LSTM models in order to check the classification of multiple labels.
Stars: ✭ 20
Labels
Projects that are alternatives of or similar to Intrusion Detection System
Tensorflow2 Generative Models
Implementations of a number of generative models in Tensorflow 2. GAN, VAE, Seq2Seq, VAEGAN, GAIA, Spectrogram Inversion. Everything is self contained in a jupyter notebook for easy export to colab.
Stars: ✭ 883 (+4315%)
Mutual labels: jupyter-notebook
Deepbayes
Bayesian methods in deep learning Summer School
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Sage
Home of the Semi-Analytic Galaxy Evolution (SAGE) galaxy formation model
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Seq 2 Seq Ocr
Handwritten text recognition with Keras
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Udacity Deep Learning Nanodegree
This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Azure Webapp W Cntk
Deployment template for Azure WebApp, CNTK, Python 3 (x64) and sample model
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Notebooks
An attempt to formalize my thoughts. A pythonic approach to mental housekeeping
Stars: ✭ 14 (-30%)
Mutual labels: jupyter-notebook
Anda
Code for our ICAR 2019 paper "ANDA: A Novel Data Augmentation Technique Applied to Salient Object Detection"
Stars: ✭ 20 (+0%)
Mutual labels: jupyter-notebook
Ud810 Intro Computer Vision
My solutions for Udacity's "Introduction to Computer Vision" MOOC
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Pytorch Bicubic Interpolation
Bicubic interpolation for PyTorch
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Attend Infer Repeat Pytorch
S.M.Ali Eslam et.al. Attend, Infer, Repeat: Fast Scene Understanding with Generative Models ICML16
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Mnist 1stclass on aznotebook
給想體驗如何在微軟AZ notebook上操作GPU及做圖像辨識(以MNIST資料集為例)
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Deep Learning Experiments
Notes and experiments to understand deep learning concepts
Stars: ✭ 883 (+4315%)
Mutual labels: jupyter-notebook
Tutorials
A project for developing tutorials for Streams
Stars: ✭ 14 (-30%)
Mutual labels: jupyter-notebook
Facealignmentcompare
Empirical Study of Recent Face Alignment Methods
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Grab Aiforsea
Entry for Grab's AI for S.E.A. challenge
Stars: ✭ 20 (+0%)
Mutual labels: jupyter-notebook
Lstm Sentiment Analysis
Sentiment Analysis with LSTMs in Tensorflow
Stars: ✭ 886 (+4330%)
Mutual labels: jupyter-notebook
Core Stories
All the notebooks for the analysis of Emotional Arcs within the Project Gutenberg corpus, see "The emotional arcs of stories are dominated by six basic shapes"
Stars: ✭ 15 (-25%)
Mutual labels: jupyter-notebook
Intrusion-Detection-System
I have tried some of the machine learning and deep learning algorithm for IDS 2017 dataset. The link for the dataset is here: http://www.unb.ca/cic/datasets/ids-2017.html. By keeping Monday as the training set and rest of the csv files as testing set, I tried one class SVM and deep CNN model to check how it works. Here the Monday dataset contains only normal data and rest of the days contains both normal and attacked data.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].