statDataAnalyzer's repositories
scaling_fl
Repo for the paper "Scaling Federated Learning for Fine-tuning of Large Language Models"
best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
awesome-controls
A collection of awesome security controls mapping for solutions across frameworks.
Awesome-Federated-Learning
Federated Learning Library: https://fedml.ai
Awesome-Meta-Learning
A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.
BioSentVec
BioWordVec & BioSentVec: pre-trained embeddings for biomedical words and sentences
citation-sorted-arxiv-slack-bot
New articles in arXiv's cs.CV, cs.LG and stat.ML, published every day by top researchers.
course20
Deep Learning for Coders, 2020, the website
Deep-learning-for-clustering-in-bioinformatics
Deep Learning-based Clustering Approaches for Bioinformatics
Deep-Learning-In-Production
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
differential-privacy-tensorflow
Samples of multi-class text classification with Differential Privacy Tensorflow 2.0
examples
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
federated
A framework for implementing federated learning
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.
KGE
Some papers on Knowledge Graph Embedding(KGE)
ml-powered-applications
Companion repository for the book Building Machine Learning Powered Applications
MLOps-Specialization-Notes
Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
PLMpapers
Must-read Papers on pre-trained language models.
pykg2vec
Python library for knowledge graph embedding and representation learning.
pyprobml
Python code for "Machine learning: a probabilistic perspective" (2nd edition)
PySyft
A library for encrypted, privacy preserving machine learning
the-elements-of-statistical-learning
My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
The-Elements-of-Statistical-Learning-Python-Notebooks
A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book