Data Mining and Machine Learning Techniques using Jupyter Notebook and Python3. 🐍

This particular Repository includes 3 folders.
Each folder is a unique project by its own, including among others some Data Mining and Machine Learning techniques.

In this Project, we were asked to kind of "play" with the given data, and we practiced more our Data Mining skills. To be more specific, we had 3 csv files, and we had to merge them together and sculpt them properly , in order to extract some useful data about some Airbnb apartments.

In the next Project, we took a step deeper into the Machine Learning techniques.
More specifically, we learned to use some classification methods, such as:

• Support Vector Machines
• Random Forests
• Naive Bayes
• K-Nearest Neighbor

Also, it must to be mentioned that the classification was implemented on differents text representations, such as:

• BoW (Bag of Words)
• Tf-idf

Last but not least, we were asked to evaluate the accuracy of each method, using 10-Fold Cross Validation, and also we did some Clustering to our data.

In the final Project, we did some of the things that we did in the previous Projects, such as cleaning and sclupting the data, but also we tried to optimize the scores of some classification models, i.e Naive Bayes.

These projects contains also explainations of each project individually and how to be implemented in greek.

This project is part of the course: Data Mining Techniques , Spring of 2020. University of Athens, DiT.