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Fotini Athanasopoulou's Projects

advanced-machine-learning icon advanced-machine-learning

This is a reoository with the code created for a course on Advanced machine learning in physics. The project was based on the Higgs ML challenge from 2012.

aima icon aima

Solutions to AIMA (Artificial Intelligence: A Modern Approach)

aima-exercises icon aima-exercises

Exercises for the book Artificial Intelligence: A Modern Approach

aima-java icon aima-java

Java implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

aima-pseudocode icon aima-pseudocode

Pseudocode descriptions of the algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

aima-python icon aima-python

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

aipnd-revision icon aipnd-revision

Revision to the code and associated files for the AI Programming with Python Nanodegree Program

algorithms icon algorithms

Bug-tracking for Jeff's algorithms book, notes, etc.

algorithms-1 icon algorithms-1

This is a continuously updating list of some of the most essential algorithms implemented in pseudocode, C++, Python and Java.

anfis-from-scratch icon anfis-from-scratch

Adaptive neuro fuzzy inference system from scratch. All codes inside, no dependency

annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

athena icon athena

General-purpose streaming I/O framework

atlas icon atlas

Quick SQLMap Tamper Suggester

autogpt icon 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.

bdt-tutorial icon bdt-tutorial

Hands-on boosted decision tree tutorial (using XGBoost) for September 2017 Fermilab Machine Learning Group Meeting.

binderhub icon binderhub

Run your code in the cloud, with technology so advanced, it feels like magic!

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