ffnn

Jingyi-Luo/Stock_Price_Movement_Prediction_RNN_CNN_FFNN

The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using transaction data from the Limit Order Book (LOB).

vkeswani/IITK_Memotion_Analysis

Bimodal and Unimodal Sentiment Analysis of Internet Memes (Image+Text)

ignis-sec/Neural-Network-with-Cpp

Simple FFNN using C++

kiranmukesh7/Face-Recognition-based-Biometric-Attendance-System

Face Recognition by Eigenface method with the trained Feed Forward Neural Network and other classifiers applied to biometric attendance system functional on static-images.

kyrcha/deep-learning-pipelines

Implementations of various deep learning pipelines

romiras/viz-mouse-gesture-recognition

Early mouse gesture recognition experiments / Delphi

shuwang127/NLP-FFNN

Feed Forward Neural Network for Sentiment Classification and Language Modeling

GvHemanth/Transformers-based-Text-Summarization

Revolutionize text summarization with this Transformer model, leveraging state-of-the-art techniques. Trained on news articles, it produces concise summaries effortlessly. Explore cutting-edge capabilities for your summarization needs.

iulianoroberto/PythonNeuralNets

Basic neural network in Python.

MagnusChase03/GoML

A simple and fast feed forward neural network library.

rconfa/Deep-Learning-Assignment

A repository of assignments performed during the Advanced Machine Learning course.

cmnarrillos/uned_DeepNetwork_tf

Benchmark for testing FeedForward Neural Networks with TensorFlow

cmnarrillos/uned_RRNN

Code developed for the tasks associated with Neural and Complex Networks subject at UNED

Darveivoldavara/yandex_practicum_projects

Данные проекты были выполнены в ходе обучения в Яндекс.Практикуме по профессии "Специалист по Data Science"

emailic/Object-Detection-Classification-CNN-COCO

Project done at the Politechnic University of Madrid together with my colleagues Anamarija Eres and Dominik Kos.

grogusbeskar/FFNN-BP-Classifier

Feed-Forward Neural Network-Based Face Classifier Model with Histogram of Oriented Gradients Feature Extraction

Jingyi-Luo/Digit_Recognizer_With_MNIST_Data_Using_FFNN

A feed forward neural network (FFNN) is built to recognize the gray-scale images of hand-drawn digits from zero through nine using tensorflow.

kiranmukesh7/Face-Detection-and-Recognition-by-Eigenface-Method

A Face Detection and Recognition system based on Eigenface method

loopiiu/Deep_Learning_Task2_Action_Recognition

Action recognition using LSTM

R40835/acronyms-and-long-forms-prediction

Classification of acronyms and their long forms using an RNN (LSTM), CNN, and FFNN model. The experiments focused on the RNN and used different vectorisation methods and hyperparameters. Models were built with Keras and the notebook code runs on Google Colab.

RaffaeleAns/AML-Assignments

A repository with Advanced Machine Learning Course Assignments (FFNN, AutoEncoders, CNN, TL, HPO)

Reema-Khaseeb/AML-multi-class-FFNN-object-classification

RhiteshKS/Neural-POS-Tagging

Designed and implemented POS taggers using Feed Forward Neural Networks and LSTMs and evaluated them using accuracy, f1 score and confusion matrix. Did extensive hyperparameter tuning to achieve high performance. INLP Assignment, Monsoon '24.

RodneyFinkel/FFNN_build

Project demonstrating how to build a simple Feed Forward Neural Network using australian weather data for a binary prediction. Activator functions and Optimizer functions coded for didactic purposes

yahyanejadalre/Project-of-Numerical-Analysis-for-Machine-Learning

This repository introduces Artificial Intelligence with a focus on Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN). Initially intended as supplementary lecture material, it helps readers understand LSTM-RNN and its evolution since the 1990s. Modern research on LSTM-RNN uses updated notations and more concise derivations.

ywan3223/Churn-Model-of-Customers

Optimizing customer retention with FFNN-based churn prediction model

angeligareta/deep-learning-basics-tf

Deep Learning basics with Tensorflow and Keras. It includes implementing deep neural networks, feed-forward neural networks, convolutional neural networks, and a traffic sign detection system, using GTSDB and CIFAR dataset.

dalip98/Machine-Learning

Consists of different types of machine learning models.

MallaSailesh/Neural_POS_Tagging

Get the Parts of Speech Tagging for the sentences using neural networks - FFNN and RNN

micheleantonazzi/bioinformatics-project

Analyze the active regulatory region of DNA using FFNN and CNN

NicholasLiem/IF3270_FP_FFNN

A quick implementation of Fast Feed Neural Network that support reading JSON input and visualize the network in an image

R40835/file-type-detection-by-byte-blocks

Deep Learning for file type Identification in Digital Forensics. We use the first, body, and last blocks of bytes on the disk to account for all possible scenarios and train the FFNN, CNN, GRU, and LSTM models. Afterward, we make predictions and evaluate the performance of each model.

raulorteg/ML-Iris-database

Made from Scratch: Logistic regression, k-means clustering and FFNN Neural Network.

u66u/supa-simple-ffnn

Supa simple feed forward neural net with explanations to practice c++ :)

Udrasht/Neural-pos-tagger

This repository includes an implementation of a neural sequence model, such as FFNN or LSTM, designed to tag words in sentences with the correct part-of-speech (POS) tags.