Jupyter Notebooks in S3 - Jupyter Contents Manager implementation

Useful scripts and notebooks for Data Science. The project was made by Miquido. https://www.miquido.com/

Credit Card Fraud Detection Model with an accuracy of 91.24%.Uses AWS for training and tuning.

Backend repo for Notebooks

Jupyter Notebook ETL from AWS S3 bucket

Recommendation System using Factorization Machines - AWS SageMaker NoteBook Instance

Jupyter notebooks to help team members utilize AWS SageMaker tools

CRUD Operation on S3 bucket from jupyter notebook using boto3.

Implement pipeline between services, notebook, aws for automate recommendation engine

Using AWS -Sagemaker to train Machine learing model directly from jupyter notebook

Big Data using PySpark, AWS, pgAdmin, postgreSQL, and Google Colab Notebooks to analyze if there any bias towards paid Amazon Reviews.

End-to-end loan eligibility prediction using XGBoost on Amazon SageMaker with data stored in S3 and tested via local notebook.

Pulled 10GB ofYelp Business data through the terminal via Kaggle API. The data was then pushed to and AWS S3 Bucket bucket for storage and analyzed on a Elastic MapReduce Cluster on a Jupyter Notebook using PySpark

End-to-end data analysis project using RDS (AWS) data sources (containing csv data), ETL/EDA + Deep Learning models in Jupyter Notebooks, and Tableau visualizations & dashboard

This repository contains different projects and deep learning concept notebooks. I mostly used PyTorch to develop ANN, RNN, CNN, GAN/DCGAN algorithms. I used AWS services such as Sagemaker, lambda, Restful API, EC2 and EMR during learning phase. 'Orca is deep diver dolphin, shows my honest approach to deep dive in the field of AI.

A learning exercise demonstrating a manual data pipeline using a Jupyter Notebook, extracting car data from an AWS S3 datalake, performing transformations with Pandas, and loading the processed data into a Dockerized PostgreSQL database.

Google Colaboratory Notebook files to design ETL pipeline of Amazon music reviews and connection to AWS PostgreSQL database and analysis of the ratio of five star reviews as it relates to participation in the Vine program.

Deploying a Sentiment Analysis Model on Amazon Sagemaker which consists of deploying a Sentiment Analysis model using Recurrent Neural Networks in the Amazon AWS SageMaker tool. The notebook and Python files provided here result in a simple web application which interacts with a deployed recurrent neural network performing sentiment analysis on …

This repository consists of 7 machine learning projects implementing various machine learning algorithms like XGBoost, LinearRegression, k-means Clustering, NLP in Amazon Sagemaker Notebook. AWS Lambda and API Gateway are used to deploy the ML models in web app.

The pipeline integrates multiple data sources web-scraped community areas, taxi trip data from the Chicago Open Data API, and weather data from Open-Meteo. It cleans, normalizes, and merges them with Python, loads the processed results to AWS S3 via Lambda, and provides interactive analysis in Jupyter notebooks.