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Using machine learning algorithms and data analysis techniques to predict the number of hatching eggs, optimize egg hatching conditions, predict optimal incubation parameters, and improve hatch rates.

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cepdnaclk/e18-6sp-ML-for-Analyzing-Egg-Hatching

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ML for Analyzing Egg Hatching


Introduction

Egg hatching is a vast biological process that depends of many factors.

Problem

Once the eggs are collected from the breeder farms they are categorized according to their external appearance. But still farmers cannot 100% sure whether an egg is going to hatch at the end of the process. Incubation is a longer process of 21 days. So, if an egg is not going to hatch at the end, it is waste of incubation space and electricity.

Solution

If we can predict the hatchablity of an egg before it is going to the incubation it is going to be economical benificial to breeder farms. So, We are expecting to develope a ML model which has the capability to do this prediction. With this farms can easily supply the required demand daily.

Also when one part of the egg collection is going to the incubation, the other part is called the rejected eggs. We are trying the predict the required management which is suitable for the farm in order to reduce the number of rejected eggs.

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Using machine learning algorithms and data analysis techniques to predict the number of hatching eggs, optimize egg hatching conditions, predict optimal incubation parameters, and improve hatch rates.

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