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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 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.
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.
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.
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
Retail data analysis pipeline utilizing AWS S3, Snowflake, Python, SQL, and Tableau. It demonstrates data transformation and setup in Jupyter Notebook, integrates real-time retail insights via an automated Tableau dashboard with Snowflake, and employs a CRON job in Jupyter Lab connected to Amazon SQS for consistent data updates.