Learn what machine learning is and get a high-level view of it with Python.

Machine Learning with Python Libraries

Machine learning is a type of artificial intelligence used with multiple Python libraries. In this module, we’ll learn to code basic machine learning models, including common algorithms such as linear regression, logistic regression, SVM, KNN, decision trees, and more. This module will teach you how to import datasets into Python using pandas. We’ll also learn about tree-based learning algorithms to predict numeric and categorical outputs. If you need to revise the concepts, we have summarized key concepts of machine learning, and the overviews of specific algorithms are dispersed throughout the module.

A Practical Guide to Machine Learning with Python

## Importance of Machine Learning?
Machine learning did not develop overnight, and the path to the present day has been anything but smooth sailing.

While it’s intriguing to see trends rise quickly, it’s important to also understand the long periods of resilience before the curve. For those pursuing a career in machine learning, it’s reassuring to know this field of study predates not only the Internet and the moon landing, but also most readers of this course.

## Evolution of Machine Learning


# Importance of Machine Learning?
Machine learning did not develop overnight, and the path to the present day has been anything but smooth sailing.

While it’s intriguing to see trends rise quickly, it’s important to also understand the long periods of resilience before the curve. For those pursuing a career in machine learning, it’s reassuring to know this field of study predates not only the Internet and the moon landing, but also most readers of this course.

# Evolution of Machine Learning


This lesson will highlight the importance and evolution of machine learning.

Before We Begin

Introduction to Machine Learning

Exploratory Data Analysis

Data Scrubbing

Pre-Model Algorithms

Split Validation

Model Design

Linear Regression

Logistic Regression

Support Vector Machines

K-Nearest Neighbors

Tree-Based Methods

Unsupervised Learning

Deep Learning

Conclusion

Appendix

Why Learn Machine Learning

Importance of Machine Learning?