Mlp Python Packages

smallmlp

SmallMLP is a library for small, nonlinear datasets ( n < 500 ). It replaces manual architecture search with adaptive hyperparameters derived from dataset parameters ( n , d , K ), and produces calibrated prediction intervals through weighted conformal prediction.

neuralnetworks

Multi-Layer Perceptrons with Fourier encoding, visualization and PyTorch compilation

nlp-text-preprocessing

This project is a comprehensive collection of NLP techniques, practical Python code, and real-world text processing workflows — designed for learners who want to master NLP fundamentals and apply them in AI/ML projects.

metaperceptron

MetaPerceptron: A Standardized Framework For Metaheuristic-Driven Multi-layer Perceptron Optimization

contextuals

A lightweight Python library providing comprehensive contextual information (time, weather, location, news, system) for AI applications with optimized prompts and graceful fallbacks

dougnet

A lightweight, deep learning library written in pure Python

complexnn

A toolbox for using complex-valued standard network modules in PyTorch, including MLP, CNN, RNN, Attention.

griffin-torch

Implementation of Griffin from the paper: "Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models"

x-mlps

Configurable MLPs built on JAX and Haiku

mantissa-mlp

Multilayer perceptrons for tabular data on the mantissa C engine — dense models on two CERN datasets, with honest speed/accuracy/RAM benchmarks vs PyTorch & TensorFlow. By Tekin Ertekin.

mantissa-nn

Shared neural-network primitives for the mantissa family on the mantissa C engine — engine binding, NumPy reference backend, and Dense/Flatten layers. Base package for cnn/mlp/auto-encoder. By Tekin Ertekin.

vision-mlp-oneflow

Vision MLP Models Based on OneFlow