Data Science On Google Cloud Platform Predictive Analytics
DOWNLOAD
Download Data Science On Google Cloud Platform Predictive Analytics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Science On Google Cloud Platform Predictive Analytics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Data Science On Google Cloud Platform Predictive Analytics
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2018
Data Science On Google Cloud Platform Predictive Analytics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Learn how to use Google Cloud Platform to train and deploy machine learning models for predictive analytics.
Data Science On Google Cloud Platform Predictive Analytics
DOWNLOAD
Author : Kumaran Ponnambalam
language : en
Publisher:
Release Date : 2018
Data Science On Google Cloud Platform Predictive Analytics written by Kumaran Ponnambalam and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Data Science On The Google Cloud Platform
DOWNLOAD
Author : Valliappa Lakshmanan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-12-12
Data Science On The Google Cloud Platform written by Valliappa Lakshmanan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-12 with Computers categories.
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You’ll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines
Practical Applications Of Data Processing Algorithms And Modeling
DOWNLOAD
Author : Whig, Pawan
language : en
Publisher: IGI Global
Release Date : 2024-04-29
Practical Applications Of Data Processing Algorithms And Modeling written by Whig, Pawan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Computers categories.
In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.
Data Science Thinking
DOWNLOAD
Author : Longbing Cao
language : en
Publisher: Springer
Release Date : 2018-08-17
Data Science Thinking written by Longbing Cao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-17 with Computers categories.
This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.
Mastering Data Science
DOWNLOAD
Author : Bright Mills
language : en
Publisher: via tolino media
Release Date : 2025-07-31
Mastering Data Science written by Bright Mills and has been published by via tolino media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-31 with Computers categories.
Data Science offers a comprehensive exploration into the expansive world of data science, tailored for students, professionals, and enthusiasts seeking to build or deepen their understanding.
1000 Platforms
DOWNLOAD
Author : Adrian Mackenzie
language : en
Publisher: Policy Press
Release Date : 2025-04-28
1000 Platforms written by Adrian Mackenzie and has been published by Policy Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-28 with Computers categories.
In today’s digital world, platforms are everywhere, shaping our social and cultural landscapes. This groundbreaking book shows how platforms are not just technical systems, but complex networks involving diverse people, practices and values. It explores a wide range of digital platforms, using insights from science and technology studies, anthropology, sociology and cultural theories to offer fresh perspectives on how platforms, media and devices function and evolve. Blending ethnographic work with technical analysis, this is essential reading for anyone wanting a deeper understanding of the digital age.
Introduction To Deep Learning Business Applications For Developers
DOWNLOAD
Author : Armando Vieira
language : en
Publisher: Apress
Release Date : 2018-05-02
Introduction To Deep Learning Business Applications For Developers written by Armando Vieira and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-02 with Computers categories.
Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You’ll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) that can be applied for image colorization, image completion, and style transfer. After reading this book you will have an overview of the exciting field of deep neural networks and an understanding of most of the major applications of deep learning. The book contains some coding examples, tricks, and insights on how to train deep learning models using the Keras framework. What You Will Learn Find out about deep learning and why it is so powerful Work with the major algorithms available to train deep learning models See the major breakthroughs in terms of applications of deep learning Run simple examples with a selection of deep learning libraries Discover the areas of impact of deep learning in business Who This Book Is For Data scientists, entrepreneurs, and business developers.
Health Informatics Practical Guide Seventh Edition
DOWNLOAD
Author : William R. Hersh
language : en
Publisher: Lulu.com
Release Date : 2018
Health Informatics Practical Guide Seventh Edition written by William R. Hersh and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Science categories.
Health informatics is the discipline concerned with the management of healthcare data and information through the application of computers and other information technologies. The field focuses more on identifying and applying information in the healthcare field and less on the technology involved. Our goal is to stimulate and educate healthcare and IT professionals and students about the key topics in this rapidly changing field. This seventh edition reflects the current knowledge in the topics listed below and provides learning objectives, key points, case studies and extensive references. Available as a paperback and eBook. Visit the textbook companion website at http://informaticseducation.org for more information.--Page 4 de la couverture.
Google Cloud Platform For Data Science
DOWNLOAD
Author : Dr. Shitalkumar R. Sukhdeve
language : en
Publisher: Apress
Release Date : 2023-12-03
Google Cloud Platform For Data Science written by Dr. Shitalkumar R. Sukhdeve and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-03 with Computers categories.
This book is your practical and comprehensive guide to learning Google Cloud Platform (GCP) for data science, using only the free tier services offered by the platform. Data science and machine learning are increasingly becoming critical to businesses of all sizes, and the cloud provides a powerful platform for these applications. GCP offers a range of data science services that can be used to store, process, and analyze large datasets, and train and deploy machine learning models. The book is organized into seven chapters covering various topics such as GCP account setup, Google Colaboratory, Big Data and Machine Learning, Data Visualization and Business Intelligence, Data Processing and Transformation, Data Analytics and Storage, and Advanced Topics. Each chapter provides step-by-step instructions and examples illustrating how to use GCP services for data science and big data projects. Readers will learn how to set up a Google Colaboratory account and run Jupyter notebooks, access GCP services and data from Colaboratory, use BigQuery for data analytics, and deploy machine learning models using Vertex AI. The book also covers how to visualize data using Looker Data Studio, run data processing pipelines using Google Cloud Dataflow and Dataprep, and store data using Google Cloud Storage and SQL. What You Will Learn Set up a GCP account and project Explore BigQuery and its use cases, including machine learning Understand Google Cloud AI Platform and its capabilities Use Vertex AI for training and deploying machine learning models Explore Google Cloud Dataproc and its use cases for big data processing Create and share data visualizations and reports with Looker Data Studio Explore Google Cloud Dataflow and its use cases for batch and stream data processing Run data processing pipelines on Cloud Dataflow Explore Google Cloud Storage and its use cases for data storage Get an introduction to Google Cloud SQL and its use cases for relational databases Get an introduction to Google Cloud Pub/Sub and its use cases for real-time data streaming Who This Book Is For Data scientists, machine learning engineers, and analysts who want to learn how to use Google Cloud Platform (GCP) for their data science and big data projects