20-deep-learning-use-cases

Here you can find twenty google colab files written for Deep Learning use cases

age-and-gender-detection

airline-delay-prediction

A project leveraging machine learning to forecast airline delays. Features a user-friendly Flask web interface for inputting flight details and receiving delay predictions.

amazon-stock-forecasting-pytorch-lstm

Amazon stock prices using a Long Short-Term Memory (LSTM) neural network implemented with PyTorch. This project leverages deep learning techniques for accurate time series forecasting.

car-price-prediction

covid-19-unemployment-analysis

covid-dashboard-using-flask

A Flask-powered platform delivering real-time data visualization and information on the COVID-19 pandemic.

custom-segmentation-using-k-means-clustering

K-Means clustering implementation for custom segmentation tasks, allowing users to group data points based on similarity for personalized analysis and insights.

ejtos-react_budget_app

react_budget_app

emotion-detection-nlp-project

Emotion detection Neural Language Processing project build with Flask web framework

face-recognition-opencv

Explore the Face Recognition with OpenCV project, a showcase of computer vision prowess. Witness real-time face recognition using OpenCV, blending Haarcascades for precise detection with a simple and extensible recognition algorithm.

fitzone-fitness-application

This is an application developed as a social media platform based suitable for add fitness routines

flask-web-framework-mini-assignment

form-validation

Developed using Kotlin

getting-started-with-git-and-github-final-project

github-final-project

health-care-chat-bot

heart-failure-prediction-pytorch-and-ann

This is a Python project utilizing PyTorch and artificial neural networks for heart failure prediction, analyzing datasets and predicting likelihood based on input features.

house-price-prediction

image-caption-generator-cnn

This project Implements a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to generate descriptive captions for input images.

image-classification-cnn

This project employs CNN for accurate image classification, leveraging deep learning techniques to recognize and categorize visual content efficiently.

image-style-transfer-vgg19

This project features Image Style Transfer using the VGG19 neural network. Style transfer merges the artistic style of one image with the content of another. Leveraging the powerful VGG19 convolutional neural network, it excels in image-related tasks.

investing_mobile_application

This is the project in mobile application development, developed by using Kotlin

iris-flower-dataset-classification-using-logistic-regression

kidney-disease-prediction

This is a machine learning project that predicts kidney disease based on clinical and laboratory features, enabling users to build and deploy predictive models.

loan-defaulter-prediction

This project aims to provide optimal solutions to a bank by cautioning against the risks associated with loan approvals for businesses. It involves exploratory data analysis, data cleaning, feature engineering, and the application of classification models to predict loan defaulters. The project achieves a 92% accuracy rate in predictions.

module-managing-page-mern-stack

A project created using MERN Stack for Module Management function

movie-recommender-system

mri-brain-tumor-detection-vgg16

This project employs the VGG16 neural network for accurate and efficient detection of brain tumors in MRI images.

named-entity-recognition-ner

This project work as a NLP tool for precise identification and classification of named entities in text. Features state-of-the-art algorithms, customizable for various domains and entity types. Ensures fast and scalable processing of large text corpora.