HudaAlQadah's Stars
public-apis/public-apis
A collective list of free APIs
PowerDataHub/terraform-aws-airflow
Terraform module to deploy an Apache Airflow cluster on AWS, backed by RDS PostgreSQL for metadata, S3 for logs and SQS as message broker with CeleryExecutor
AnandDedha/aws-airflow-dataengineering-pipeline
anthonywong611/Batch-ETL-with-AWS-EMR-and-MWAA
Create a data pipeline on AWS to execute batch processing in a Spark cluster provisioned by Amazon EMR. ETL using managed airflow: extracts data from S3, transform data using spark, load transformed data back to S3.
im-nsk/Building-an-Automated-Weather-Data-Pipeline-with-Airflow-From-Ingestion-to-Data-Warehouse
This project focuses on building a robust data pipeline using Apache Airflow to automate the ingestion of weather data from the OpenWeatherAPI and loading it into a data warehouse, specifically AWS Redshift.
gersongerardcruz/temperature_forecasting_airflow_automation
This is an end-to-end temperature forecasting pipeline with API data collection automated with Apache Airflow, AWS EC2, AWS S3, and Python
aws/aws-mwaa-local-runner
This repository provides a command line interface (CLI) utility that replicates an Amazon Managed Workflows for Apache Airflow (MWAA) environment locally.
FRC4188/Edge_Computing
A repository holding Jupyter Notebooks and Python code to train and deploy custom machine learning models for Edge Computing devices
gigwegbe/tinyml-papers-and-projects
This is a list of interesting papers and projects about TinyML.
crespum/edge-ai
A curated list of resources for embedded AI
mGalarnyk/datasciencecoursera
Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.
anujagro/ML-MultiClass-Classification-with-GridSearchCV-and-10-Fold-Cross-Validation
ML MultiClass Classification with GridSearchCV and 10 Fold Cross-Validation ( Regularised Logistic Regression, KNN, SVM,
jddunn/dementia-progression-analysis
Alzheimer's / dementia progression classifier for MRIs using CNNs and transfer learning
shahidzikria/ADD-Net
Alzheimer’s Disease (AD) is a neurological brain disorder marked by dementia and neurological dysfunction that affects memory, behavioral patterns, and reasoning. Alzheimer’s disease is an incurable disease that primarily affects people over the age of 40. Presently, Alzheimer’s disease is diagnosed through a manual evaluation of a patient’s MRI scan and neuro-psychological examinations. Deep Learning (DL), a type of Artificial Intelligence (AI), has pioneered new approaches to automate medical image diagnosis. The goal of this study is to create a reliable and efficient approach for classifying AD using MRI by applying the deep Convolutional Neural Network (CNN). In this paper, we propose a new CNN architecture for detecting AD with relatively few parameters and the proposed solution is ideal for training a smaller dataset. This proposed model successfully distinguishes the early stages of Alzheimer’s disease and shows class activation maps as a heat map on the brain. The proposed Alzheimer’s Disease Detection Network (ADD-Net) is built from scratch to precisely classify the stages of AD by decreasing parameters and calculation costs. The Kaggle MRI image dataset has a significant class imbalance problem and we exploited a synthetic oversampling technique to evenly distribute the image among the classes to prevent the problem of class imbalance. The proposed ADD-Net is extensively evaluated against DenseNet169, VGG19, and InceptionResNet V2 using precision, recall, F1-score, Area Under the Curve (AUC), and loss. The ADD-Net achieved the following values for evaluation metrics: 98.63%, 99.76%, 98.61%, 98.63%, 98.58%, and 0.0549 for accuracy, AUC , F1-score, precision, recall, and loss, respectively. From the simulation results, it is noted that the proposed ADD-Net outperforms other state-of-the-art models in all the evaluation metrics.
khalil-research/PyEPO
A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming
ClaudioPoli/Optimization-techniques
Set of projects implemented for the "decision models and optimization" University course
kabirkhan/edx_learner_attrition
Optimized pipeline for predicting specific dropout rates for learners in Microsoft edX courses
IBM/optimize-procurement-and-inventory-with-ai
Create a web application that uses the IBM Decision Optimization's prescriptive analytics model, to choose which plant to order items from
SamDLearn/Decision-Optimization
Most popular Business problems solving implemented with python
raovivek34/Airbnb-Business-Analysis-of-New-York-and-Austin-2019
Price Optimization Model for Airbnb, which helps Airbnb hosts set the right price for their Airbnb listing and provides customers, the benefit of cost. This is a Regression Analysis problem.
fatosmorina/machine-learning-exams
This repository contains links to machine learning exams, homework assignments, and exercises that can help you test your understanding.
openedx-unsupported/edx-analytics-pipeline
nishant-sg/Machine-Learning-Algorithms
ozzieliu/python-tutorials
Tutorials of data science concepts and packages in Python
randylaosat/Predicting-Employee-Turnover-Complete-Guide-Analysis
Understand why employees leave a company and apply various machine learning models to predict the next leaver!
AnggaPradiktas/productivity-prediction-of-garment-employees