Pro Machine Learning Algorithms : A Hands-On Approach to Implementing Algorithms in Python and R

Arnold

ISBN 10: 1484235630 / ISBN 13: 9781484235638

Verlag: Apress, 2018

Beschreibung

Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Bestandsnummer des Verkäufers ABNR-209277

Bibliografische Details

• Titel: Pro Machine Learning Algorithms : A Hands-On Approach to Implementing Algorithms in Python and R
• Verlag: Apress
• Veröffentlichungsdatum: 2018
• Sprache: Englisch
• ISBN-10: 1484235630
• ISBN-13: 9781484235638
• Bindung: Softcover
• Ausgabe: Internationale Ausgabe
• Zustand: New

Über diesen Titel

Inhaltsangabe

Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a practical understanding of all the levers that can be tuned in a model, before implementing the models in Python/R.

You will cover all the major algorithms: supervised and unsupervised learning, which include linear/logistic regression; k-means clustering; PCA; recommender system; decision tree; random forest; GBM; and neural networks. You will also be exposed to the latest in deep learning through CNNs, RNNs, and word2vec for text mining. You will be learning not only the algorithms, but also the concepts of feature engineering to maximize the performance of a model. You will see the theory along with case studies, such as sentiment classification, fraud detection, recommender systems, and image recognition, so that you get the best of both theory and practice for the vast majority of the machine learning algorithms used in industry. Along with learning the algorithms, you will also be exposed to running machine-learning models on all the major cloud service providers.

You are expected to have minimal knowledge of statistics/software programming and by the end of this book you should be able to work on a machine learning project with confidence. 

What You Will Learn

• Get an in-depth understanding of all the major machine learning and deep learning algorithms 
  
• Fully appreciate the pitfalls to avoid while building models
  
• Implement machine learning algorithms in the cloud 
  
• Follow a hands-on approach through case studies for each algorithm
• Gain the tricks of ensemble learning to build more accurate models
• Discover the basics of programming in R/Python and the Keras framework for deep learning

Who This Book Is For

Business analysts/ IT professionals who want to transition into data science roles. Data scientists who want to solidify their knowledge in machine learning.

Über die Autorin bzw. den Autor

V Kishore Ayyadevara currently leads retail analytics consulting in a start-up. He received his MBA from IIM Calcutta. Following that, he worked for American Express in risk management and in Amazon's supply chain analytics teams. He is passionate about leveraging data to make informed decisions - faster and more accurately. Kishore's interests include identifying business problems that can be solved using data, simplifying the complexity within data science and applying data science to achieve quantifiable business results.