This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

Understanding the effects of data parallelism and sparsity on neural network training

Neural Network Training Fingerprint (NNTF) is a visualization approach to analyze the training process of any neural network performing classification.

Neural network for recognizing handwritten numbers

Conjunto de ferramentas para lidar com treinamentos de redes neurais artificiais

🧠 Automated neural network ablation studies using LLM agents and LangGraph. Systematically remove components, test performance, and gain insights into architecture importance through an intelligent multi-agent workflow.

Modifies a neural network's hyperparameters, activation functions, cost functions, and regularization methods to improve training performance and generalization.

This notebook provides source code of my work for my Master's Thesis.

An Open Source Machine Learning Framework for Everyone

Real-time Object Detection and Neural Network Training Visualization

This repository documents the process of finding the optimal learning rate for deep neural networks

Simple implementation of a 3 layer MLP network using numpy.

Modifies a neural network's hyperparameters, activation functions, cost functions, and regularization methods to improve training performance and generalization.

Build Autonomous multi agent system collaborating with models to spot deals and notify you of special bargains. It uses both Agent and Workflow approach. Uses tools in loop to achieve desired results and send notification to users.

A memory-efficient, gradient-free zeroth-order (derivative-free) optimizer designed to solve the "Curse of Dimensionality" in Black-Box optimization and memory-constrained Machine Learning. It provides an O(log D) gradient estimation approach that can successfully train Neural Networks without ever calculating analytical derivatives or Backprop