Data Analysis with Python for Beginners - Ep 7: Predictive Analysis (Linear Regressions)
In this episode, we’ll learn how to perform predictive analysis using linear regressions. Linear regressions are one of the most common ways of making predictions for future values of a dataset. Knowing how to make linear regressions is a hugely valuable skill in data analysis/data science!
Matplotlib website/documentation: https://matplotlib.org/stable/index.html
Seaborn website/documentation: https://seaborn.pydata.org/
This video is part of an 8-part course designed to give absolute beginners an idea of what Data Analysis looks like using Python.
What is Data Analysis? Data Analysis is the process of exploring, cleaning, transforming, and modeling data as a way to produce insightful conclusions or gather useful information. It is a field that is growing rapidly, along with Data Science, and one that is very high in demand. If you’re interested in taking that career route, or maybe just want to learn it as a skill, this course is for you!
This episode’s Colab Notebook: https://colab.research.google.com/dri...
AI Global Index Dataset: https://www.kaggle.com/datasets/kater...
Episode Timestamps:
00:00 - Intro
00:28 - Linear function overview
1:40 - What is linear regression?
04:06 - sklearn library
04:45 - Selecting regression variables
06:48 - Train/test splits
09:22 - Creating/training model
10:12 - Getting linear equation
11:49 - Scoring model
14:23 - Creating/visualizing predictions
16:44 - Plotting linear regression
20:16 - Multiple Linear Regressions