Serverless Machine Learning for Titanic Dataset
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Updated
Nov 21, 2022 - Python
Serverless Machine Learning for Titanic Dataset
Predicting Snow Conditions in Passo Tonale (Trento, Italy)
Backfill historical OHLC feature in a Feature Store (Hopsworks) using an orchestration tool (Prefect).
A simple app to help you find relevant machine learning papers to read.
Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)
shows how to backfill Energy Consumption feature in a Feature Store (Hopsworks) using an orchestration tool (Prefect).
Terraform module that creates the required cloud resources for Hopsworks.ai clusters on AWS and AZURE.
FastRide: NYC Taxi Trip Duration Prediction employs machine learning techniques to accurately predict the duration of taxi trips in New York City, helping transportation businesses optimize operations and enhance customer satisfaction.
A study project to explore Hopsworks - a fraud detection classifier. The project was inspired by one of the tutorials available in the Hopsworks documentation.
Go SDK to interact with the Hopsworks API
🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴
The work uses Hopsworks for Feature store and creating Feature groups for Machine learning modeling
Forecasting Ethereum return quantiles using a handful of different statistical learning models and selecting the best based on out of sample error. Hopsworks feature store and model registry is used to automate the process. Ethereum quantile returns are predicted daily and displayed on a Streamlit dashboard.
Hopsworks.ai Terraform provider
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