Dive into the world of machine learning and create projects with real-world applications
Key Features
- Build a face recognition application from scratch
- Prepare and train your data for your projects
- Learn real-world applications of your algorithms
Book Description
Machine learning is a field of computer science through which you can create complex models that perform multiple functions using mathematical input. Python is a popular choice to create machine learning models due to a plethora of libraries easily accessible. This course takes you through this impressive combination of Python and machine learning, teaching you the basics of machine learning to create your own projects.
You'll begin learning about different types of machine learning models and how to choose the relevant ones for your project. You'll learn to optimize this model and apply performance metrics to track its performance. You'll also learn topics like regression, classification, and clustering to improve the performance of your model. You'll learn the basics of neural networks and use scikit-learn to perform calculations in your project.
By the end of this course, you'll have created a face recognition application using everything you've learned in this course.
The code bundle for this course is available at https://github.com/PacktPublishing/Python-Machine-Learning-Crash-Course-for-Beginners
What you will learn
- Train different types of machine learning models for your project
- Prepare and clean data for your project
- Optimize your machine learning model to best suit your project needs
- Build your own machine learning model from scratch
- Apply performance metrics to track the performance of your model
- Use scikit-learn to perform calculations in your project
Who this book is for
This course is for Python developers who are new in the field of machine learning. No prior knowledge or experience of machine learning is required. A basic understanding of Python programming will be needed here.
