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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).
Bimodal and Unimodal Sentiment Analysis of Internet Memes (Image+Text)
Face Recognition by Eigenface method with the trained Feed Forward Neural Network and other classifiers applied to biometric attendance system functional on static-images.
Implementations of various deep learning pipelines
Early mouse gesture recognition experiments / Delphi
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.
Basic neural network in Python.
A repository of assignments performed during the Advanced Machine Learning course.
Feed Forward Neural Network for Sentiment Classification and Language Modeling
Benchmark for testing FeedForward Neural Networks with TensorFlow
Code developed for the tasks associated with Neural and Complex Networks subject at UNED
Данные проекты были выполнены в ходе обучения в Яндекс.Практикуме по профессии "Специалист по Data Science"
Project done at the Politechnic University of Madrid together with my colleagues Anamarija Eres and Dominik Kos.
Feed-Forward Neural Network-Based Face Classifier Model with Histogram of Oriented Gradients Feature Extraction
A feed forward neural network (FFNN) is built to recognize the gray-scale images of hand-drawn digits from zero through nine using tensorflow.
A Face Detection and Recognition system based on Eigenface method
Action recognition using LSTM
Web UI for the data behind PicPic, an automatic image selection tool for news articles
Fully Connected Forward Feed Neural Network
A repository with Advanced Machine Learning Course Assignments (FFNN, AutoEncoders, CNN, TL, HPO)
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
Optimizing customer retention with FFNN-based churn prediction model
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.
Consists of different types of machine learning models.
Classic SMT and feed-forward neural networks: LT2212 V19 Assignment 4 group Rho
Analyze the active regulatory region of DNA using FFNN and CNN
A quick implementation of Fast Feed Neural Network that support reading JSON input and visualize the network in an image
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.
Made from Scratch: Logistic regression, k-means clustering and FFNN Neural Network.
Supa simple feed forward neural net with explanations to practice c++ :)
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.