Step-by-Step Machine Learning with Python
Easy-to-follow examples that get you up and running with machine learning
Created by Yuxi (Hayden) Liu
Get hands-on with machine learning using Python by working through practical, real-world examples. You'll explore key concepts like data analysis, preprocessing, feature extraction, and model evaluation, all while building your own predictive models from scratch. By the end, you'll have a solid grasp of the machine learning ecosystem and best practices for applying these techniques.
Packt | Sep 2017 | 296 min
What You Will Learn
You'll start by setting up your Python environment and learning the basics of machine learning. As you progress, you'll dive into hands-on projects that guide you through each step, from data exploration to building and evaluating models. Each topic is reinforced with practical examples, helping you gain confidence and experience with Python's machine learning tools.
Key Features
- Build and evaluate machine learning models for real-world data problems
- Apply Python tools for data analysis, visualization, and feature extraction
- Understand and implement core algorithms for classification and regression
Target Audience
Ideal for those with a basic understanding of Python who want to move into data science or machine learning roles. If you're looking to apply machine learning to real problems and want to learn by doing, you'll find this course fits your goals. It's designed for learners ready to deepen their technical skills and build practical, job-ready knowledge.
