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ReAct Agent
A project exploring ReAct agents. The main project is a GPT-based ReAct agent with access to a Python REPL and function retrieval, enabling simple workflows by chaining API calls. A second project demonstrates a minimal ReAct agent using OpenAI function calling.
Python REPL ReAct Agent » OpenAI function-calling ReAct agent »
Implementing Gaussian processes
A blog series exploring Gaussian processes. It starts by building intuition with from-scratch implementations in Python, then moves to a practical example using TensorFlow Probability on a real-world problem.
Implement Gaussian Processes »
Multi-armed bandit implementation
Learn the basics of Bayesian multi-armed bandit models by implementing a simple example in Python.
Implement a multi-armed bandit »
Implementing neural networks from scratch
The first section gradually builds a feedforward neural network from scratch in Python using NumPy. It starts by explaining gradient descent on basic models, then adds hidden layers with nonlinearities, backpropagation, and momentum.
The second section implements a recurrent neural network (RNN) in Python using NumPy. It explains the basics of backpropagation through time (BPTT) and discusses challenges in training recurrent networks.
Regression quattro stagioni
Linear regression parameter estimation implemented in four ways: simple linear regression, ordinary least squares (OLS), gradient descent, and Markov chain Monte Carlo (MCMC).
Implement linear regression four ways »