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Detecting Respiratory Diseases via Audio samples using Deep Learning and Librosa
Machine Learning - - Supervised, Unsupervised, and deep learning. Processing data for features, training models, assess performance, and tune parameters for better performance. In the process, you'll get an introduction to natural language processing, image processing, and popular libraries such as Spark and Keras.
Focused on advancing credit card fraud detection, this project employs machine learning algorithms, including neural networks and decision trees, to enhance fraud prevention in the banking sector. It serves as the final project for a Data Science course at the University of Ottawa in 2023.
This repo introduces word embeddings. It contains complete code to train word embeddings from scratch on a small dataset.
Image Semantic Segmentation
poverty prediction and analysis
A system that uses deep learning LSTM model to predict the price increase or decrease of one or more stocks for the next three months.
Fashion Recommendation System using Deep Learning
Permet de creer avec Tensorflow et Keras un recommandeur de hastag pour image, avec des algorithmes de deep learning.
Various applications of deep learning have been demonstrated.
The project is focused on building Classification Model using Convolution Neural Network for classifying the images into "Horse" and "Human".
Given the parameters such as - Year of sale of the house, The age of the house at the time of sale, Distance from city center, Number of stores in the locality, The latitude, The longitude this project is to predict the price of the house.
A Fraud Prediction Model
Optimization of Neural Network using Keras Tuner
templates of keras official pretrained model instances