Analyze the active regulatory region of DNA using FFNN and CNN
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Updated
Mar 29, 2021 - Python
Analyze the active regulatory region of DNA using FFNN and CNN
A feed forward neural network (FFNN) is built to recognize the gray-scale images of hand-drawn digits from zero through nine using tensorflow.
Web UI for the data behind PicPic, an automatic image selection tool for news articles
A repository with Advanced Machine Learning Course Assignments (FFNN, AutoEncoders, CNN, TL, HPO)
Feed-Forward Neural Network-Based Face Classifier Model with Histogram of Oriented Gradients Feature Extraction
Project done at the Politechnic University of Madrid together with my colleagues Anamarija Eres and Dominik Kos.
Данные проекты были выполнены в ходе обучения в Яндекс.Практикуме по профессии "Специалист по Data Science"
Supa simple feed forward neural net with explanations to practice c++ :)
A Face Detection and Recognition system based on Eigenface method
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.
Consists of different types of machine learning models.
Made from Scratch: Logistic regression, k-means clustering and FFNN Neural Network.
Optimizing customer retention with FFNN-based churn prediction model
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.
A quick implementation of Fast Feed Neural Network that support reading JSON input and visualize the network in an image
Action recognition using LSTM
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.
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