A multiverse of Prophet models for timeseries
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Updated
Sep 11, 2024 - Python
A multiverse of Prophet models for timeseries
Base classes for creating scikit-learn-like parametric objects, and tools for working with them.
RFE BSU organization of data processing labs
Predicting price trends in crypto (BTC_USDT) using lstm, rnn, sklearn, sktime, tff, etc.
🌀 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
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
Time series anomaly detection, time series classification & dynamic time warping, performed on a dataset of Canadian weather measurements.
Develop a solution for analyzing and visualizing power system load monitoring data.
Learn about how we can use models to make predicitons in the future based on historical data.
🧱 Wrappers for 3rd party models to be used with fold (https://github.com/dream-faster/fold)
Machine learning model for a forecast of taxi orders in the next hour
Time Series Classification experiments on open-source datasets using Automated Machine Learning (AutoML) frameworks
Evaluation Practices done for the Time Series Forecasting subject
Hyperparametrization test with a genetic algorithm
Personal notes about the sktime framework
Análise do dataset da Olist
A guide to Sktime framework (with Jupyter notebook)
A collection of notebooks for my final year project. The notebooks are used to create a virtual personal trainer to check bicep curls, squats and overhead presses.
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