With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.
Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with st...
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.
Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics.
This pocket reference includes sections that cover:
• Classification, using the Titanic dataset
• Cleaning data and dealing with missing data
• Exploratory data analysis
• Common preprocessing steps using sample data
• Selecting features useful to the model
• Model selection
• Metrics and classification evaluation
• Regression examples using k-nearest neighbor, decision trees, boosting, and more
• Metrics for regression evaluation
• Clustering
• Dimensionality reduction
• Scikit-learn pipelines
Welcome to Tanto Cyber - Cybersecurity & IT Solutions! 🚀
To access all the features and facilities we provide, please log in first using your account.
By using TantoCyber.com, you agree to comply with the applicable rules for the safety and convenience of everyone.
Thank you for being part of our community! 🔒✨
Tanto Cyber: A platform sharing free eBooks & tech insights, focusing on cybersecurity and knowledge.
