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cybersecurity_datascience

This project documents how to analyze cybersecurity data with machine learning tools and techniques in python. The tutorials run in Jupyter Notebooks and depend on the environment described in the environment.yml file.

deep-belief-network

A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility

deep-hybrid-models

Deep hybrid models: bridging discriminative and generative approaches https://cs.stanford.edu/~ermon/papers/uai2017_cr.pdf

deep-learning-for-hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

deep-learning-models

Implementations of popular deep learning models in Theano+Lasagne

deep-learning-with-keras

Code repository for Deep Learning with Keras published by Packt

deep-outlier-detection

Deep distance-based outlier detection published in KDD18: Learning representations specifically for distance-based outlier detection. Few-shot outlier detection

deepadots

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

deepids

Playing around with IDS data in Keras

deeponeclass

Deep learning based one class classification code targeting one class image classification. Tests carried out on Abnormal image detection, Novel image detection and Active Authentication reported state of the art results.

dlaicourse

Notebooks for learning deep learning

dsu_insure_sp19_ids_prioritization

IDS Alert Prioritization INSuRE Research Project

edge-detect

Repository for IEEE CCNC'21 paper titled "Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural Network".

electricity-price-forecasting-using-hybrid-model

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_right:

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

feature-engineering-live-sessions

featureimportance

Some experiments with sklearn feature importance

fraud-detection-in-credit-card-transactions-using-machine-learning-techniques

Classification of fraudulent credit card transactions.

getting-things-done-with-pytorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

hackers-guide-to-deep-learning

Tutorials on how to engineer Machine Learning projects using Deep Neural Networks with PyTorch and Python

ibm_data_science_professional_certificate

This repo contains all the files created or used in this course

icmr

ICMR Sponsored Seminar On Deep Learning Techniques and Tools for Medical Applications

ids

IDS with CICIDS2017 dataset based on tree-based classifiers

ids-unsw-nb15

IoT intrusion Detection Model based on neural network and random forests

ids-unsw-nb15-1

Building an Intrusion Detection System on UNSW-NB15 Dataset Based on Machine Learning Algorithm

ids_iot

Intrusion Detection System (IDS) for IoT as my early intern in third engineer year

imbalance_class_sklearn

Address imbalance classes in machine learning projects.

introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

intrusion-detection-big-data