placing your order...
Don't refresh or navigate away from the page.
- customers also bought these items
- Graph-Powered Machine Learning
- Interpretable AI
- Feature Engineering Bookcamp
- Human-in-the-Loop Machine Learning
- Machine Learning Engineering in Action
choose your plan
pro
monthly
annual
$24.99
$249.99
only $20.83 per month
- share your subscription with one other person
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Ensemble Methods for Machine Learning ebook for free
Ensemble Methods for Machine Learning ebook for free
team
monthly
annual
$49.99
$499.99
only $41.67 per month
- five seats for your team
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Ensemble Methods for Machine Learning ebook for free
Ensemble Methods for Machine Learning (print + eBook) added to cart
continue shopping
adding to cart
choose your plan
pro
monthly
annual
$24.99
$249.99
only $20.83 per month
- share your subscription with one other person
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Ensemble Methods for Machine Learning ebook for free
team
monthly
annual
$49.99
$499.99
only $41.67 per month
- five seats for your team
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Ensemble Methods for Machine Learning ebook for free
An excellent guide to ensemble learning with concepts, code, and examples.
Look inside
Ensemble machine learning combines the power of multiple machine learning approaches, working together to deliver models that are highly performant and highly accurate.
Inside Ensemble Methods for Machine Learning you will find:
Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you’ll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits, limitations, and practical methods of applying ensemble machine learning to real-world data, and be ready to build more explainable ML systems.
Inside Ensemble Methods for Machine Learning you will find:
- Methods for classification, regression, and recommendations
- Sophisticated off-the-shelf ensemble implementations
- Random forests, boosting, and gradient boosting
- Feature engineering and ensemble diversity
- Interpretability and explainability for ensemble methods
Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you’ll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits, limitations, and practical methods of applying ensemble machine learning to real-world data, and be ready to build more explainable ML systems.
about the technology
Automatically compare, contrast, and blend the output from multiple models to squeeze the best results from your data. Ensemble machine learning applies a “wisdom of crowds” method that dodges the inaccuracies and limitations of a single model. By basing responses on multiple perspectives, this innovative approach can deliver robust predictions even without massive datasets.about the book
Ensemble Methods for Machine Learning teaches you practical techniques for applying multiple ML approaches simultaneously. Each chapter contains a unique case study that demonstrates a fully functional ensemble method, with examples including medical diagnosis, sentiment analysis, handwriting classification, and more. There’s no complex math or theory—you’ll learn in a visuals-first manner, with ample code for easy experimentation!FREE domestic shipping on orders of three or more print books
Extremely valuable for more complex scenarios that single models aren’t able to accurately capture.
Ensemble methods are a valuable tool. I can aggregate the strengths from multiple methods while mitigating their individual weaknesses and increasing model performance.
Step by step and with clear descriptions. Very understandable.
related titles
related titles
