multilayer-perceptron-network

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Fake Image Detection Using Machine Learning

PyTorch tutorial for learners

In this project is presented a simple method to train an MLP neural network for audio signals. The trained model can be exported on a Raspberry Pi (2 or superior suggested) to classify audio signal registered with USB microphone

Gene2Vec: Distributed Representation of Genes Based on Co-Expression

The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.

Machine Learning Library, written in J

Simple multilayer perceptron c++ implementation.

Multi class audio classification using Deep Learning (MLP, CNN): The objective of this project is to build a multi class classifier to identify sound of a bee, cricket or noise.

Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutations to increase returns and reduce risk. Trained the model using a Multilayer Perceptron Neural Network on a vast set of features that influence the stock market indices. Performed technical analysis using historical stock prices and fundamental analysis using social media dat

Tensorflow Examples

algorithm for study: multi-layer-perceptron, cluster-graph, cnn, rnn, restricted boltzmann machine, bayesian network

Various implementations and projects on CNN, RNN, LSTM, GAN, etc

A comparison between humans, neuroevolution and multilayer perceptrons playing Flapy Bird implemented in Python

A program that allows you to translate neural networks created with Keras to fuzzy logic programs, in order to tune these networks from a given dataset.

To make Tutor Landing page, used Vuex, Boostrap-vue, i18n packages. Blog pages, FAQ, Multi-Language, etc.

face recognition with deep learning

Transcriptome long-read orientation with Deep Learning

Silver Medal Solution for Shopee - Price Match Guarantee competition on Kaggle

Machine learning library for classification tasks

Collection of Machine Learning Algorithms and related Example

Machine learning library for classification tasks

A trading bitcoin agent was created with deep reinforcement learning implementations. Various experiments were performed on the type of neural network, the type of reinforcement learning algorithm and the number of daily input values that initially required from agent to make the first decision. Also, the agent was made with the assumption that for each day could ‘Sell’ or ‘Buy’.

Artificial neural networks (BCM, BAM, MLP, SOM, etc.)

Tutorial: A Feed Forward Neural Network with Backpropagation in just a few Lines of Python Code

Multilayer neural network framework implementation, used for classification and regression task. Can use multiple activation functions with backpropagation based on autograd library. Contains polynomial activation function for regression task.

Implementação simples da rede neural Perceptron Multicamadas em Javascript.

Capstone Project: Bank Customer Classification System

contains exercise solution