Machine Learning in Python

My learning journey in Machine Learning with Python.

02-study

Structure:

00Fundamental_en.ipynb Notebook with key essentials

00Fundamental_en.html HTML generated from notebook

01Numpy_en.ipynb Concepts and some practical examples with numpy

01Numpy_en.html HTML generated from notebook

02MatplotlibSeaborn_en.ipynb Concepts and practical examples with matplotlib and seaborn libraries

02MatplotlibSeaborn_en.html HTML generated from notebook

03Pandas_en.ipynb Concepts and practical examples with pandas library

03Pandas_en.html HTML generated from notebook

Pandas study suggestion (links): 10 minutes to pandas / Cookbook

04ScikitLearn_en.ipynb Concepts and practical examples with Scikit-Learn library

04ScikitLean_en.html HTML generated from notebook

04DataReport.html Example html generated via pandas profiling

05StatsModels(timeSeries)_en.ipynb Concepts and practical examples with Stats Models library in Time series

05StatsModels(timeSeries)_en.htmlHTML generated from notebook

03-data

Some csv files

Structure:

air_passengers.csv

sampledata.xls

winequality.xls

05-images

Images used in repository