Catalog Search Results
Author
Pub. Date
[2019]
Language
English
Description
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R's syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics...
Author
Pub. Date
[2018]
Language
English
Description
Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples, so you can learn fundamental concepts with AI solutions and apply them to your own projects. People tend to talk about AI as something mystical and...
Author
Pub. Date
[2018]
Edition
First edition.
Language
English
Description
Machine learning can be a difficult subject if you're not familiar with the basics. With this book, you'll get a solid foundation of introductory principles used in machine learning with the statistical programming language R. You'll start with the basics like regression, then move into more advanced topics like neural networks, and finally delve into the frontier of machine learning in the R world with packages like Caret. By developing a familiarity...
75) Machine learning in production: developing and optimizing data science workflows and applications
Author
Pub. Date
[2019]
Language
English
Author
Language
English
Description
Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. "Deep learning with R, second edition" is a...
Author
Pub. Date
2019.
Language
English
Description
Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Along the way, you will be introduced to many popular open-source frameworks, like SciPy, scikitlearn, Numba, Apache Spark, etc. The book is structured around examples, so you will grasp...
Author
Pub. Date
[2019]
Language
English
Description
"Deep learning handles the toughest search challenges, including imprecise search terms, badly indexed data, and retrieving images with minimal metadata. And with modern tools like DL4J and TensorFlow, you can apply powerful DL techniques without a deep background in data science or natural language processing (NLP). This book will show you how. "Deep learning for search" teaches you to improve your search results with neural networks. You'll...
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