Intro to Machine Learning with Python: A Hands-On Guide to Building Intelligent Systems Using Python
Unlock the world of machine learning with this hands-on guide designed to teach you the fundamentals of building intelligent systems using Python. Whether you're new to machine learning or have some experience, this beginner-friendly book will walk you through practical examples, starting from scratch and moving toward more advanced techniques.
Learn how to build machine learning models, train them with data, and make predictions-all using the power of Python and its libraries like scikit-learn, TensorFlow, and Keras.
What you'll learn:
The basics of machine learning and its real-world applications
How to prepare and clean your data for training machine learning models
Use Python libraries such as scikit-learn, Pandas, and NumPy for data manipulation and model building
Implement supervised learning techniques like linear regression, classification, and support vector machines
Explore unsupervised learning techniques such as k-means clustering and principal component analysis
Train, test, and evaluate models using metrics like accuracy, precision, and recall
Build and deploy machine learning models into production using Flask and Django
Understand deep learning with TensorFlow and Keras
By the end of this book, you'll be able to create powerful machine learning systems and apply them to real-world problems using Python.
Perfect for beginners who want to start building intelligent systems with Python and machine learning.
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