Treball de fi de grau sobre tècniques d'aprenentatge profund aplicades a la classificació d'escenaris de xarxes oportunistes
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Updated
May 12, 2023 - Jupyter Notebook
Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.
Treball de fi de grau sobre tècniques d'aprenentatge profund aplicades a la classificació d'escenaris de xarxes oportunistes
A C# implementation of ANNs
This project focuses on the presence of any kind of recurrence behaviour in a tissue sample, gathered from a an already diagnosed patient for Prostate Cancer
Experiments with Scene Labeling using Recurrent Convolutional Neural Networks on Foraminifera and Unity simulated images for Segmentation task
Markdown of my blog posts at medium.com/@hackintoshrao and hackintoshrao.com
Deep Learning Models written in Tensorflow
Image classification task with Convolutional Neural Networks using Keras and dataset gathered from Kaggle. By following a great tutorial.
Programming assignments of the course
Scaffold codes for feedforward neural network and autoencoders.
Code for Michael Nielsen 's notes
Reinforcement Learning Techniques
Only Applications of (feed-forward, convolution, LSTMs)Deep learning with Keras.
Deep Neural Network