Hands-on ensemble learning with Python : build highly optimized ensemble machine learning models using scikit-learn and Keras [E-Book] / George Kyriakides, Konstantinos G. Margaritis.
Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models.
Saved in:
Full text |
|
Personal Name(s): | Kyriakides, George, author |
Margaritis, Konstantinos G., author | |
Edition: |
1st edition |
Imprint: |
Birmingham :
Packt Publishing,
2019
|
Physical Description: |
284 pages (online resource) |
Note: |
englisch |
ISBN: |
9781789612851 9781789617887 |
Subject (ZB): | |
Subject (LOC): | |
Classification: |
LEADER | 02547nam a2200385 i 4500 | ||
---|---|---|---|
001 | PACKT0005368 | ||
008 | 200212s2019 ob 000 0 eng d | ||
020 | |a 9781789612851 | ||
020 | |a 9781789617887 | ||
035 | |a (Sirsi) a803243 | ||
041 | 0 | |a eng | |
082 | 0 | 0 | |a 006.31 |
084 | 0 | |a DOL - Programming language - Python | |
084 | 0 | |a DYA - Artificial intelligence | |
100 | 1 | |a Kyriakides, George, |e author | |
245 | 1 | 0 | |a Hands-on ensemble learning with Python : |b build highly optimized ensemble machine learning models using scikit-learn and Keras |h [E-Book] / |c George Kyriakides, Konstantinos G. Margaritis. |
250 | |a 1st edition | ||
264 | 1 | |a Birmingham : |b Packt Publishing, |c 2019 |e (Packt) |f Packt20200417 | |
300 | |a 284 pages (online resource) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
500 | |a englisch | ||
505 | 0 | |a Hands-on ensemble learning with Python : build highly optimized ensemble machine learning models using scikit-learn and Keras -- Contributors -- Table of Contents -- Preface -- Section 1: Introduction and Required Software Tools -- Chapter 1: A Machine Learning Refresher -- Chapter 2: Getting Started with Ensemble Learning -- Section 2: Non-Generative Methods -- Chapter 3: Voting -- Chapter 4: Stacking -- Section 3: Generative Methods -- Chapter 5: Bagging -- Chapter 6: Boosting -- Chapter 7: Random Forests -- Section 4: Clustering -- Chapter 8: Clustering -- Section 5: Real World Applications -- Chapter 9: Classifying Fraudulent Transactions -- Chapter 10: Predicting Bitcoin Prices -- Chapter 11: Evaluating Sentiment on Twitter -- Chapter 12: Recommending Movies with Keras -- Chapter 13: Clustering World Happiness -- Another Book You May Enjoy -- Index. | |
520 | 3 | |a Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models. | |
596 | |a 1 | ||
650 | 0 | |a Big Data and Business Intelligence | |
650 | 0 | |a Machine learning. | |
650 | 0 | |a Python (Computer program language) | |
650 | 4 | |a machine learning | |
650 | 4 | |a Python (programming language) | |
700 | 1 | |a Margaritis, Konstantinos G., |e author | |
856 | 4 | 0 | |u http://portal.igpublish.com/iglibrary/search/PACKT0005368.html |z Volltext |
915 | |a zzwFZJ3 | ||
949 | |a XX(803243.1) |w AUTO |c 1 |i 803243-1001 |l ELECTRONIC |m ZB |r N |s Y |t E-BOOK |u 17/4/2020 |x UNKNOWN |z UNKNOWN |1 ONLINE |