Full School21 Piscine: Python and intro to Data Science
This repository contains my projects done for Python Data science Piscine at Ecole 42/ School 21.
Day00: We learn how to use curl, sort, uniq, jq, sed and cat for data collection and preprocessing
Day01: Basic syntax and semantics of Python
Day02: Basic OOP in Python
Day03: Virtual environment and different Python libraries
Day04: Python: list comprehension, map, filter, reduce, counter, generator
Day05: Introduction to pandas library
Day06: Intro to basic SQL queries
Day07: Matplotlib, Seaborn, Plotly
Day08: Machine learning in Python
Day09: Machine learning in Python
Rush00: We are creating first analytical report in jupyter notebook. We analyze data from the given Mpvielens database. For this purpose we create classes and methods (description is given in subject). We use that module to create the report.
Rush01: This is the best part of the Piscine! We are writing the programm which could predict how tasty a dish can be with the products currently in our refrigerator, gives us the nutrition facts and links with recepies. The work contains 3 parts: research, development and the program itself. For the researchwe prepare data from given files. We use some algorithms of regression and classification and choose the best one. In the development we create classes and methods which will use the created model, connect to the given links and get the nutrition facts of the product (using the API) and recipes (via Beautifulsoup). The it gives us all the information we need.
