Rajesh Kalakoti's repositories
loghub
A large collection of system log datasets for AI-driven log analytics [ISSRE'23]
Espionage
A Linux Packet Sniffing Suite for Automated MiTM Attacks
awesome-python
An opinionated list of awesome Python frameworks, libraries, software and resources.
datascience
Curated list of Python resources for data science.
Practical-Deep-Learning-at-Scale-with-MLFlow
Practical Deep Learning at Scale with MLFlow, published by Packt
data_mining_with_R
Data mining with R from scratch for autumn semester
component-library
The goal of CLAIMED is to enable low-code/no-code rapid prototyping style programming to seamlessly CI/CD into production.
awesome-graph-explainability-papers
Papers about explainability of GNNs
adversarial-explainable-ai
đź’ˇ Adversarial attacks on explanations and how to defend them
Azure-Databricks-Cookbook
Azure Databricks Cookbook, Published by Packt
data-pipelines-with-apache-airflow
Code for Data Pipelines with Apache Airflow
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Federated_socket_programming
Federated Learning Demo in Python using Socket Programming
fed_iot_guard
Detection of IoT devices infected by malwares from their network communications, using federated machine learning
DataScienceR
a curated list of R tutorials for Data Science, NLP and Machine Learning
SciPy-Recipes
Code repository for SciPy Recipes, published by Packt
pytorch_active_learning
PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book
Advanced-Deep-Learning-with-Python
Advanced Deep Learning with Python by Packt Publishing
pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
deep-learning-with-pytorch
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
acv00
ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
Applied-Machine-Learning-Explainability-Techniques
Applied Machine Learning Explainability Techniques, published by Packt
AIX360
Interpretability and explainability of data and machine learning models
Quantus-XAI-metrics-
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams