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battleships_game

For the very first project we created a Battleship game with Python. The work flowchart and coding logic have also been included in the repository.

daft_212

diamonds

Project Week 4 with Daniel & Ting

docs

sampling

final_project_airbnb_pricing_in_paris

By acquiring data with Airbnb Scraper, we plotted the distribution of airbnb listings in Paris and investigated the patterns of several features and their impact on machine learning predictions on the listing's pricing range. 7 machine learning models were tested and an average accuracy rate of 65-70% has been reached.

ironhacklabs_ting

netflix

We took the data from Netflix and performed several supervised machine learning models in the hope of finding relevant patterns and dependencies of the data features and its target variable. The rating and vote range of Netflix titles could be predicted with around 60% of accuracy rate.

project1_soldier-dice-risk-

project_5_streamlit

With the dataset on chest pain information we explored insight related to gender, pain type and their implications on heart diseases. The result is demonstrated with the help of streamlit.

project_6_swift

project_8_uber

Unsupervised learning executed on Uber pickups data in NYC. Clusters of pickup spots have been plotted on maps and further insights from our observations have also been concluded.

project_week2_creating_database

For this project we explored business related data focusing on the ease of doing business in EU from World Bank and used the prepared data to create a databses with MySQL.

project_week3_data_cleaning