Machine Learning and Data Science with Python: A Complete Beginners Guide

Preview this course

This course will be mainly focusing on machine learning algorithms. Throughout this course, we are preparing our machine to make it ready for a prediction test.

Unlimited access to 750+ courses.
Enjoy a Free Trial. Cancel Anytime.

- OR -

30-Day Money-Back Guarantee
Full Lifetime Access.
56 on-demand videos & exercises
Level: All Levels
English
10hrs 19mins
Access on mobile, web and TV

What to know about this course

Artificial intelligence, machine learning, and deep learning neural networks are the most used terms in the technology world today. They're also the most misunderstood and confused terms. Artificial intelligence is a broad spectrum of science that tries to make machines intelligent like humans, while machine learning and neural networks are two subsets that sit within this vast machine learning platform. But in this course, you will focus mainly on machine learning, which will include preparing your machine to make it ready for a prediction test. You will be using Python as your programming language. Python is a great tool for the development of programs that perform data analysis and prediction. It has a variety of classes and features that perform complex mathematical analyses and provide solutions in just a few lines of code, making it easier for you to get up to speed with data science and machine learning. Machine learning and data science jobs are among the most lucrative in the technology industry in recent times. Exploring this course will help you get well-versed with essential concepts and prepare you for a career in these fields. All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-and-Data-Science-with-Python-A-Complete-Beginners-Guide

Who's this course for?

This course is for beginners who are interested in machine learning using Python.

What you'll learn

  • Install Python and required libraries.
  • Choose the best machine learning model.
  • Automate and combine workflows with pipeline.
  • Look at performance improvement with ensembles.
  • Study performance improvement with algorithm parameter tuning.
  • Finalize a machine learning project.

Key Features

  • Learn machine learning and data science using Python.
  • A practical course designed for beginners who are interested in machine learning using Python.
  • Work on predictions and case studies.

Course Curriculum

About the Author

Data Circuit