Additional information
by Booker Blunt (Author), Boozman Richard (Author)
Unlock the world of artificial intelligence and data science with this beginner-friendly guide to machine learning using Python.
This practical book takes you through everything you need to know to start building intelligent systems that can analyze data, make predictions, and learn from experience. Whether you're new to programming or looking to expand your data science skills, you'll learn how to apply machine learning techniques to real-world problems.
What you'll learn:
How to set up your Python environment for data science
The fundamentals of machine learning algorithms and how they work
How to clean, preprocess, and visualize data
Building your first machine learning models using scikit-learn
How to evaluate model performance and improve accuracy
Real-world use cases, including classification, regression, and clustering
The basics of deep learning and neural networks for advanced projects
By the end of this book, you'll be able to build and train machine learning models, analyze large datasets, and start applying AI techniques to real-world problems.
Perfect for beginners, students, and anyone looking to dive into the world of machine learning with Python.
