Data Analysis From Scratch With Python: Step By Step Guide

9. Supervised & Unsupervised Learning
What is Supervised Learning?
What is Unsupervised Learning?
How to Approach a Problem
10. Regression
Simple Linear Regression
Multiple Linear Regression
Decision Tree
Random Forest
11. Classification
Logistic Regression
K-Nearest Neighbors
Decision Tree Classification
Random Forest Classification
12. Clustering
Goals & Uses of Clustering
K-Means Clustering
Anomaly Detection
13. Association Rule Learning
Explanation
Apriori
14. Reinforcement Learning
What is Reinforcement Learning?
Comparison with Supervised & Unsupervised Learning
Applying Reinforcement Learning
15. Artificial Neural Networks
An Idea of How the Brain Works
Potential & Constraints
Here’s an Example
16. Natural Language Processing
Analyzing Words & Sentiments
Using NLTK

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Thank you !
Sources & References
Software, libraries, & programming language
Datasets
Online books, tutorials, & other references
Thank you !

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Introduction
Why read on? First, you’ll learn how to use Python in data analysis (which is a
bit cooler and a bit more advanced than using Microsoft Excel). Second, you’ll
also learn how to gain the mindset of a real data analyst (computational
thinking).
More importantly, you’ll learn how Python and machine learning applies to real
world problems (business, science, market research, technology, manufacturing,
retail, financial). We’ll provide several examples on how modern methods of
data analysis fit in with approaching and solving modern problems.
This is important because the massive influx of data provides us with more
opportunities to gain insights and make an impact in almost any field. This
recent phenomenon also provides new challenges that require new technologies
and approaches. In addition, this also requires new skills and mindsets to
successfully navigate through the challenges and successfully tap the fullest
potential of the opportunities being presented to us.
For now, forget about getting the “sexiest job of the 21st century” (data scientist,
machine learning engineer, etc.). Forget about the fears about artificial
intelligence eradicating jobs and the entire human race. This is all about learning
(in the truest sense of the word) and solving real world problems.
We are here to create solutions and take advantage of new technologies to make
better decisions and hopefully make our lives easier. And this starts at building a
strong foundation so we can better face the challenges and master advanced
concepts.

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