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 R Deep Learning Essentials
Key Features
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Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
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Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
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Build models relating to neural
... | | Developing Microservices with Node.js
Key Features
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Real world example explained chapter after chapter with code examples.
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Useful concepts for other languages like Java or PHP
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Easy to follow by people with little to none experience in Node.js
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Node.js Version 0.12.2 and the latest compatible versions of Seneca and
... | | TypeScript Design Patterns
Key Features
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This step-by-step guide will would demonstrate all the important design patterns in practice
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This book is the only documentation on the market focusing on design patterns in TypeScript
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This book is packed with rich examples that will improve...
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Microservices: Flexible Software Architecture
The Most Complete, Practical, and Actionable Guide to Microservices
Going beyond mere theory and marketing hype, Eberhard Wolff presents all the knowledge you need to capture the full benefits of this emerging paradigm. He illuminates... | | Deep Learning with Python: A Hands-on Introduction
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often ... | | Enterprise Content and Search Management for Building Digital Platforms
Provides modern enterprises with the tools to create a robust digital platform utilizing proven best practices, practical models, and time-tested techniques
Contemporary business organizations can either embrace the digital revolution—or be left behind. Enterprise Content and Search Management for Building Digital... |
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