noambassat / gemstones_project

Data Science final project

Contact: [email protected]

ML Gemstones Project

Find genstones by a given location
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Data Science project about crystals and gemstones

PROJECT PRESENTION: Gemstones_project_Presention.pdf

Step 1: Obtaining data: Gemstons_Obtaining_Data Data crawling. Main tools: Selenium Webdriver and BeautifulSoup

Step 2: Cleaning and formating the data: Step_2_Scrubbing_Data.ipynb

Step 3: Visualization: Step_3_Exploring_Data.ipynb. Main tools: pyplot, seaborn.

Step 4: Modeling: Step 4 - Clustering and Modeling Data.ipynb Clustering the data into 8 groups, by Kmeans algorithm (Unsupervised). Machine learning model: Comparison of the performance of 3 supervised algorithms: RandomForestClassifier, DecisionTreeClassifier, and KNN, using Sklearn.

Step 5: Understanding the results + Final machine learning model (based on DecisionTreeClassifier): Step 5 - interpreting Data.ipynb

Accuracy on train data 0.99 Accuracy on test data 0.97