TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)
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Updated
Jun 26, 2018 - Jupyter Notebook
TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)
App that detects severity of Diabetic Retinopathy using TensorflowLite model trained from scratch in Google Colab notebook.
Collection of notebooks I made on deep learning topics.
The notebook in the repo can be considered as a tutorial for building a CNN using pytorch.
Jupyter Notebook projects in Python coded during my Computer Vision and Pattern Recognition course at AIUB, focusing on core computer vision techniques.
Jupyter notebooks implementing Deep Learning algorithms in Keras and Tensorflow
A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.
Notes and Jupyter notebooks exploring deep learning and Tensorflow framework
Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Convolutional Neural Network (CNN) that classifies Dogs, Cats, and Pandas, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ02
Several notebooks that cover various ML concepts such LR, CNN's, RNN's, & more!
A Jupyter Notebook π equipped with code π» for identifying the position of digits π’ in a Sudoku puzzle π§© and solving it β . The notebook implements algorithms βοΈ for Sudoku puzzle solving, offering a practical tool π οΈ for enthusiasts π€ and learners π alike to explore and understand Sudoku solving techniques π§ . 2-2 METHODS FOR BOTH TASKS π.
CNN applied on Cifar-10 database.
In this project we present an image classifier with a CNN (convolutional neural network) that can detect characters from the famous TV-series "The Simpsons". The work and code is presented in a python notebook.
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