NASA Project; Plastic Marine Debris Classification-Machine Learning Software

NASA Project; I Developed Plastic Marine Debris Classification-Machine Learning Software. Plastic, metal, etc. in this software. various waste and garbage; Classified by seasons, by photos they have, by country, by date (year) and shoreline name, with high accuracy, precision, sharpness and f1 results. The models were carefully prepared and examined one by one. Damages in the data have been corrected and made suitable for artificial intelligence. Some (.dot) files have a high number of megabytes and strings, so (.png) was uploaded unformatted due to my insufficient resources. This software has been prepared by me personally for the NASA Project.

With this project, plastic, metal, etc. found in marine debris. I have provided the classification of derivative wastes according to various parameters (date, country, etc.). The machine learning software I have created works with high accuracy (The highest classification model accuracy rate is about 97%). The project regularizes the irregularity of the various data and solves the complex plastic proportions in which country they occur, in what year.

The values you enter should be (respectively):

Example: model_nasa_emirhan = ExtraTreesClassifier(criterion="gini", max_depth=None, max_features="auto", random_state=84, n_estimators=10, n_jobs=-1, verbose=0, class_weight="balanced")

Outpot : 0.9788235294117648 x 1 0.978506841585555 0.9788235294117648 0.9783583602026715 Index(['Country_Change'], dtype='object') Extra Trees in forest :) 1 saved as dot file 0 Extra Trees in forest :) 2 saved as dot file 1 Extra Trees in forest :) 3 saved as dot file 2 Extra Trees in forest :) 4 saved as dot file 3 Extra Trees in forest :) 5 saved as dot file 4 Extra Trees in forest :) 6 saved as dot file 5 Extra Trees in forest :) 7 saved as dot file 6`` Extra Trees in forest :) 8 saved as dot file 7 Extra Trees in forest :) 9 saved as dot file 8 Extra Trees in forest :) 10 saved as dot file 9 Process finished with exit code 0

I am happy to present this software to you!

Data Source: DataSource ###The coding language used:

Python >= 3.9.6

###Libraries Used:

Sklearn

Pandas

Numpy

Developer Information:

Name-Surname: Emirhan BULUT

Contact (Email) : emirhan.bulut@turkiyeyapayzeka.com

LinkedIn : https://www.linkedin.com/in/artificialintelligencebulut/

Official Website: Machine Learning Specialist- Emirhan BULUT

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Machine Learning Specialist- Emirhan BULUT Emirhan bulut Welcome to my personal portfolio website. On this website, I will tell you about my projects, my vision and my mission. I will share videos about my work in machine learning and artificial intelligence. REFERENCES "Emir is driven machine learning programmer. He recently conducted a Machine Learning Program for CO2 emissions. View this on Machine Learning Specialist- Emirhan BULUT >

Kaggle: NASA Project; Marine Debris Machine Learning

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NASA Project; Marine Debris Machine Learning NASA Project; Plastic Marine Debris Classification-Machine Learning Software View this on Kaggle >

Github: GitHub - emirhanai/NASA-Project-Plastic-Marine-Debris-Classification-Machine-Learning-Software: NASA Project; Plastic Marine Debris Classification-Machine Learning Software

GitHub		remove preview
GitHub - emirhanai/NASA-Project-Plastic-Marine-Debris-Classification-Machine-Learning-Software: NASA Project; Plastic Marine Debris Classification-Machine Learning Software NASA Project; I Developed Plastic Marine Debris Classification-Machine Learning Software. Plastic, metal, etc. in this software. various waste and garbage; Classified by seasons, by photos they have, by country, by date (year) and shoreline name, with high accuracy, precision, sharpness and f1 results. The models were carefully prepared and examined one by one. View this on GitHub >