In this repository I'll be uploading my first Python exercises that I'm currently doing in the Google Colab platform while learning Big data and Machine Learning
In the folder BigD - M5 - 2023-05-02 you can find the next files:
Jesus - M5 - 01 - Python Notebook.ipynb file contains a brief review of the types of variables and conditionals
Jesus - M5 - 02 - Condicionales.ipynb contains only three conditional exercises
Jesus - M4 - 10 - Pandas.ipynb is the file for introduction exercises of the Pandas library
Jesus - M5 - 03 - Bucles.ipynb is the testing chamber for while and for loops
In the folder BigD - M5 - 2023-05-03 you can find the next files:
Jesus - SpaceX - 2 - EDA.ipynb is the file where I obtain data from SpaceX launches to learn basic commands to transform the data collected in the Pandas library from Python
Jesus - SpaceX - 4 - EDA with Data Visualization.ipynb are the first data visulalization graphics with the seaborn y matplotlib libraries
In the folder BigD - M5 - 2023-05-04 you can find the next files:
Jesus - M5 - 06 - Introducción a Machine Learning con Scikit-Learn.ipynb in this file I tried to improve some ML models with simple methods
Jesus - M5 - 09 - Folium.ipynb (This file is only inicialized and readed but not completed)
Jesus - Prophet - Predecir el valor de Bitcoin.ipynb in this file I implemented the Prophet model to the values of the Bitcoin currency to predict how it could perform the next year
In the folder BigD - M5 - 2023-05-05 you can find the next files:
Jesus - M5 - SPACEX2 - 5 - Interactive Visual Analytics con Folium.ipynb I practiced with the Folium library in Python to visualize the SpaceX launches sites, and if the different launches were a success or not
Jesus - M5 - SPACEX2 - 6 - Machine Learning Predicciones.ipynb in this file I compared the accuracy of some predictive models in Python after I trained with a shortened SpaceX data