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In this project, I will use a linear regression algorithm to train a model and make a prediction of water temperature based on the salinity data

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CalCOFI Salinity/Temperature - Regression ML

In this project, I will use linear regression algorithm to train a model and make prediction of water temperature based on the salinity data

CalCOFI dataset

The CalCOFI data set represents the longest (1949-present) and most complete (more than 50,000 sampling stations) time series of oceanographic and larval fish data in the world. It includes abundance data on the larvae of over 250 species of fish; larval length frequency data and egg abundance data on key commercial species; and oceanographic and plankton data. The physical, chemical, and biological data collected at regular time and space intervals quickly became valuable for documenting climatic cycles in the California Current and a range of biological responses to them. CalCOFI research drew world attention to the biological response to the dramatic Pacific-warming event in 1957-58 and introduced the term “El Niño” into the scientific literature. (resource)

CalCOFI Database Tables Description - Cast Table - link

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In this project, I will use a linear regression algorithm to train a model and make a prediction of water temperature based on the salinity data

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