Lyt når som helst, hvor som helst

Nyd den ubegrænsede adgang til tusindvis af spændende e- og lydbøger - helt gratis

  • Lyt og læs så meget du har lyst til
  • Opdag et kæmpe bibliotek fyldt med fortællinger
  • Eksklusive titler + Mofibo Originals
  • Opsig når som helst
Start tilbuddet
DK - Details page - Device banner - 894x1036

Ensemble Machine Learning: A beginner's guide that combines powerful machine learning algorithms to build optimized models

Sprog
Engelsk
Format
Kategori

Fakta

An effective guide to using ensemble techniques to enhance machine learning models

About This Book • Learn how to maximize popular machine learning algorithms such as random forests, decision trees, AdaBoost, K-nearest neighbor, and more

• Get a practical approach to building efficient machine learning models using ensemble techniques with real-world use cases

• Implement concepts such as boosting, bagging, and stacking ensemble methods to improve your model prediction accuracy

Who This Book Is For

This book is for data scientists, machine learning practitioners, and deep learning enthusiasts who want to implement ensemble techniques and make a deep dive into the world of machine learning algorithms. You are expected to understand Python code and have a basic knowledge of probability theories, statistics, and linear algebra.

What You Will Learn • Understand why bagging improves classification and regression performance

• Get to grips with implementing AdaBoost and different variants of this algorithm

• See the bootstrap method and its application to bagging

• Perform regression on Boston housing data using scikit-learn and NumPy

• Know how to use Random forest for IRIS data classification

• Get to grips with the classification of sonar dataset using KNN, Perceptron, and Logistic Regression

• Discover how to improve prediction accuracy by fine-tuning the model parameters

• Master the analysis of a trained predictive model for over-fitting/under-fitting cases

In Detail

Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior prediction power. This book will show you how you can use many weak algorithms to make a strong predictive model. This book contains Python code for different machine learning algorithms so that you can easily understand and implement it in your own systems.

This book covers different machine learning algorithms that are widely used in the practical world to make predictions and classifications. It addresses different aspects of a prediction framework, such as data pre-processing, model training, validation of the model, and more. You will gain knowledge of different machine learning aspects such as bagging (decision trees and random forests), Boosting (Ada-boost) and stacking (a combination of bagging and boosting algorithms).

Then you'll learn how to implement them by building ensemble models using TensorFlow and Python libraries such as scikit-learn and NumPy. As machine learning touches almost every field of the digital world, you'll see how these algorithms can be used in different applications such as computer vision, speech recognition, making recommendations, grouping and document classification, fitting regression on data, and more.

By the end of this book, you'll understand how to combine machine learning algorithms to work behind the scenes and reduce challenges and common problems.

Style and approach

This comprehensive guide offers the perfect blend of theory, examples, and implementations of real-world use cases.

© 2017 Packt Publishing (E-bog): 9781788294539

Release date

E-bog: 21. december 2017

Andre kan også lide...

  1. The Deep Learning Revolution Terrence J. Sejnowski
  2. Machine Learning: Deep Learning, Text Analytics, and Reinforcement Learning with Big Data David Feldspar
  3. Python: - The Bible- 3 Manuscripts in 1 book: Python Programming for Beginners - Python Programming for Intermediates - Python Programming for Advanced Maurice J. Thompson
  4. Data Science John D. Kelleher
  5. Machine Learning Introbooks Team
  6. The Creativity Code: How AI is learning to write, paint and think Marcus du Sautoy
  7. Deep Learning John D. Kelleher
  8. Selfsimilar Processes Paul Embrechts
  9. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World Karim R. Lakhani
  10. How Smart Machines Think Sean Gerrish
  11. On the Future: Prospects for Humanity Martin Rees
  12. Deep Learning: Machine Learning and Data Analytics Explained David Feldspar
  13. Artificial Intelligence Explained Introbooks Team
  14. Theory of Games and Economic Behavior: 60th Anniversary Commemorative Edition John von Neumann
  15. The Age of AI: Artificial Intelligence and the Future of Humanity Jason Thacker
  16. Robot-Proof: Higher Education in the Age of Artificial Intelligence Joseph E. Aoun
  17. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are Seth Stephens-Davidowitz
  18. From Startup to Exit: An Insider's Guide to Launching and Scaling Your Tech Business Shirish Nadkarni
  19. Human Universe Professor Brian Cox
  20. The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity Byron Reese
  21. When Computers Were Human David Alan Grier
  22. Game Theory: Understanding the Mathematics of Life Brian Clegg
  23. Ultimate Python for Fintech Solutions Bhagvan Kommadi
  24. The Grand Contraption: The World as Myth, Number, and Chance David Park
  25. Artificial Intelligence: The Insights You Need from Harvard Business Review Andrew McAfee
  26. Python Essentials For Dummies Alan Simpson
  27. Coding for Beginners Using Python: A HANDS-ON, PROJECT-BASED INTRODUCTION TO LEARN CODING WITH PYTHON MARK MATTHES AND ERIC LUTZ
  28. Individual-based Modeling and Ecology Steven F. Railsback
  29. Java Programming Simplified: Fundamental of Object-Oriented Language and Addition of a Guide on the C++ Language Eddy Romansky
  30. Introducing Python: Modern Computing in Simple Packages, 2nd Edition Bill Lubanovic
  31. Python for Beginners: A Crash Course Guide to Learn Python in 1 Week Timothy C. Needham
  32. Python Computer Programming: Simple Step-By-Step Introduction to the Python Object-Oriented Programming. Quick Start Guide for beginners. Alex Campbell
  33. The Python Programming Revolution: Scripting Success: Practical Approaches to Python Programming David Lee
  34. Coders: Who They Are, What They Think and How They Are Changing Our World Clive Thompson
  35. Python Programming Language. Introduction for Beginners: Your Path to Coding Mastery James Ferry
  36. Elegant Python: Simplifying Complex Solutions Michael Huang
  37. Java Fundamentals Introbooks Team
  38. Fundamentals of Software Architecture: An Engineering Approach Neal Ford
  39. Ultimate Flutter for Cross-Platform App Development Temidayo Adefioye
  40. Computational Thinking Peter J. Denning
  41. The Weather Machine: A Journey Inside the Forecast Andrew Blum
  42. Mastering OpenCV with Python Ayush Vaishya
  43. Atoms and Ashes: A Global History of Nuclear Disasters Serhii Plokhy
  44. The World According to Physics Jim Al-Khalili
  45. Astrophysics for People in a Hurry Neil deGrasse Tyson
  46. Permanent Record: A Memoir of a Reluctant Whistleblower Edward Snowden

Vælg dit abonnement

  • Over 600.000 titler

  • Download og nyd titler offline

  • Eksklusive titler + Mofibo Originals

  • Børnevenligt miljø (Kids Mode)

  • Det er nemt at opsige når som helst

Flex

For dig som vil prøve Mofibo.

89 kr. /måned
  • 1 konto

  • 20 timer/måned

  • Gem op til 100 ubrugte timer

  • Eksklusivt indhold hver uge

  • Fri lytning til podcasts

  • Ingen binding

Prøv gratis
Den mest populære

Premium

For dig som lytter og læser ofte.

129 kr. /måned
  • 1 konto

  • 100 timer/måned

  • Eksklusivt indhold hver uge

  • Fri lytning til podcasts

  • Ingen binding

Start tilbuddet

Unlimited

For dig som lytter og læser ubegrænset.

149 kr. /måned
  • 1 konto

  • Ubegrænset adgang

  • Eksklusivt indhold hver uge

  • Fri lytning til podcasts

  • Ingen binding

Start tilbuddet

Family

For dig som ønsker at dele historier med familien.

Fra 179 kr. /måned
  • 2-6 konti

  • 100 timer/måned pr. konto

  • Fri lytning til podcasts

  • Kun 39 kr. pr. ekstra konto

  • Ingen binding

2 konti

179 kr. /måned
Prøv gratis