Artificial Neural Networks with R using keras, neuralnet and functional API.
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Updated
May 1, 2020 - R
Artificial Neural Networks with R using keras, neuralnet and functional API.
Keras functional api on DonorsChoose dataset.
This is my take on the Wine Quality Dataset. (Multi Label problem)
Predict whether a DonorsChoose.org project proposal submitted by a teacher will be approved.
Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.
This repository contains my solutions for the Coursera course TensorFlow: Advanced Techniques Specialization. Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scen…
Neural Network to estimate wine's quality and its type
Git repository for the following video: https://www.youtube.com/watch?v=qj4NHdX2wfI&feature=youtu.be
I showcase that I have broad set of skills regarding machine learning algorithms since I use Logistic Regression, XGBoost and Neural Networks in this project. Especially that I have a good understanding regarding neural networks and the Keras library.
Digital Image Processing Course | Home Works Design| Fall 2021 | Dr. MohammadReza Mohammadi
This repository contains application of functional api and sequential api for the hello world dataset in computer vision
The goal of this project is to build a neural network that takes an MNIST handwritten digit (0-9) image and a random number (digit 0-9) as inputs and returns the predicted class label (0-9) for the input image and its addition (sum) with the input random number as summed output (range 0-18) label as outputs.
Prediction of acute inflammations of urinary bladder and acute nephritises using UCI Acute Inflammations Data Set.
TensorFlow: Advanced Techniques Specialization by Laurence Moroney, and Eddy Shyu in Coursera by DeapLearning.AI
Tensorflow 2: for Deep Learning Specialization | Imperial College London
This deep learning project focuses on building a robust air quality classifier from photos using two different deep learning architectures.
Convolutional Neural Network project for sign language detection.
Age and Gender prediction from facial images using VGG16 and the Keras Functional API.
Streamlit Demo of CIFAR10 Data Classifiers
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