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Fruit Count prediction using its shape and size using Machine Learning

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Project name

Fruit Prediction using its size and shape

Installation Required

  1. Scikit-learn
  2. Python3
  3. Jypyter notebook

Description

In this project we are making a prediction of fruits type by its given attributes size and shape (in given dataset) using machine learning algorithm.

Steps

1.Firstly Collect datasets of fruits and apply preprocessing on it an make data in structured format remove noisy and irrelevant data from datasets in form of excel sheets(.csv file) 2.Then using pandas make categorical data in into further insightful information including frequency, mean, median, count etc. After that using seaborn modules visualize data into form of bar graph, boxplot scatter matrix and gain some insightful information for further prediction. 3.Split data into train and test set and make a machine learning model on it by applying four important ml algorithms on it. Check which have better accuracy and result

  1. Logistic Regression.
  2. Decision Tree.
  3. K-Nearest Neighbors.
  4. Gaussian Naive Bayes Make model and choose algorithms and predict the result.