Fotini Athanasopoulou's repositories
ML-YouTube-Courses
📺 Discover the latest machine learning / AI courses on YouTube.
AIPND-revision
Revision to the code and associated files for the AI Programming with Python Nanodegree Program
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
big-ann-benchmarks
Framework for evaluating ANNS algorithms on billion scale datasets.
binderhub
Run your code in the cloud, with technology so advanced, it feels like magic!
cmssw
CMS Offline Software
codespaces-jupyter
Explore machine learning and data science with Codespaces
cpython
The Python programming language
cuda-samples
Samples for CUDA Developers which demonstrates features in CUDA Toolkit
cudf
cuDF - GPU DataFrame Library
data-science-from-scratch
code for Data Science From Scratch book
ExtractGPT
Attribute Value Extraction using Large Language Models
geant4
Geant4 toolkit for the simulation of the passage of particles through matter - NIM A 506 (2003) 250-303
geodata-in-python-oct2023
Learn the basics of geospatial data theory, covering raster, vector, and related concepts. Gain hands-on experience with Python libraries for geospatial data.
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.
hep-resources
Extended online version of the PDG Particle Physics Information review.
HEPML-LivingReview
Living Review of Machine Learning for Particle Physics
linearboost-classifier
LinearBoost Classifier is a rapid and accurate classification algorithm that builds upon a very fast, linear classifier.
MachineLearning
Basic Machine Learning and Deep Learning
ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
root
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
scikit-learn
scikit-learn: machine learning in Python
self-rewarding-lm-pytorch
Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TMVA
Toolkit for Multivariate Analysis with ROOT
wdl
Workflow Description Language - Specification and Implementations
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow