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ramcqueary
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🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.
LinkedIn_AIHawk is a tool that automates the jobs application process on LinkedIn. Utilizing artificial intelligence, it enables users to apply for multiple job offers in an automated and personali…
Code for "Approaching Deep Learning through the Spectral Dynamics of Weights"
Google's common Java, C and JavaScript library for parsing, formatting, and validating international phone numbers.
LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data. 🤖📈
Python library for Multi-Armed Bandits
TensorDict is a pytorch dedicated tensor container.
A complement to pgvector for high performance, cost efficient vector search on large workloads.
IPython und Python Programmierung
A robust web archive analytics toolkit
A Python and Command-Line Interface to Archive.org
A Baby Robot's Guide to Reinforcement Learning
University assignments and sandbox projects connected to machine learning study.
A multi-armed bandit (MAB) simulation library in Python
Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.
The official code release for Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo, ICLR 2024.
This program deploys Thompson Bandit algorithm to solve an ad prediction for highest probability of clicking.
Variety of Multi-Arm Bandit (MAB) algorithms using classic and advanced strategies, including tools for experiments and simulations in stationary and nonstationary environments
Using SciKit Learn few Deep Learning Rules and Algorithms are implemented
Reinforcement Learning (COMP 579) Project
An implementation of the Epsilon Greedy and Thompson Sampling algorithms using NumPy, pandas and Matplotlib.
This repository is focused on my assignments solutions for the Statistical Techniques for Data Science course at Innopolis University.
The simulation of Epsilon-Greedy and Thompson Sampling algorithms for Bayesian A/B Testing. The project shows how both algorithms find the optimal bandit and approximate the rewards of each bandit,…