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Udemy - Bite-Sized Data Science with Python Introduction

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File Name
Size
01 Welcome, information about this course/001 Introduction.mp4
4.8 MB
02 Setting up Python and Libraries/001 File and command to install all necessary libraries at once, with pip.html
1.4 kB
02 Setting up Python and Libraries/001 If you already have Python installed.mp4
28 MB
02 Setting up Python and Libraries/002 Links to help you install pip.html
1.9 kB
02 Setting up Python and Libraries/002 The libraries, explained.mp4
21 MB
02 Setting up Python and Libraries/003 If you want to install Python and the libraries at once.mp4
11 MB
03 Our data set the Parkinsons Telemedicine Dataset/001 Downloading the data.mp4
31 MB
03 Our data set the Parkinsons Telemedicine Dataset/002 A quick explanation of the dataset.mp4
20 MB
04 Starting our analysis/001 Starting a new iPython Notebook.mp4
25 MB
04 Starting our analysis/002 Loading the data into our iPython Notebook.mp4
20 MB
05 Manipulating data with pandas, the data analysis library/001 Coding Exercise summary statistics.html
2.1 kB
05 Manipulating data with pandas, the data analysis library/001 DataFrames are data tables.mp4
19 MB
05 Manipulating data with pandas, the data analysis library/002 Series are single rows or columns of data.mp4
33 MB
05 Manipulating data with pandas, the data analysis library/003 Slicing DataFrames to get the data we need.mp4
23 MB
05 Manipulating data with pandas, the data analysis library/004 Keeping track of the variable names we need.mp4
18 MB
06 Visualizing the data to understand it better before modeling/001 Coding exercise a single correlation.html
1.7 kB
06 Visualizing the data to understand it better before modeling/001 Looking at the datas distributions with box plots and histograms.mp4
19 MB
06 Visualizing the data to understand it better before modeling/002 Seeing multicolinearity with a scatter plot matrix.mp4
28 MB
07 Transforming the data to prepare it for modeling/001 Coding exercise practicing apply.html
1.7 kB
07 Transforming the data to prepare it for modeling/001 Taking care of multicolinearity.mp4
19 MB
07 Transforming the data to prepare it for modeling/002 Log transforming data to take care of skewed distributions.mp4
61 MB
08 Modeling the data/001 Applying a multiple regression to answer the ultimate question.mp4
36 MB
09 Conclusion/001 Download the data and iPython notebook that was used throughout this lecture.html
1.5 kB
09 Conclusion/001 Thank you.mp4
3.2 MB