Data Science On Google Cloud Platform Exploratory Data Analytics

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Data Science On Google Cloud Platform Exploratory Data Analytics

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Author :
language : en
Publisher:
Release Date : 2018

Data Science On Google Cloud Platform Exploratory Data 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 conduct exploratory data analytics on Google Cloud Platform.

Data Science On Google Cloud Platform Exploratory Data Analytics

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Author : Kumaran Ponnambalam
language : en
Publisher:
Release Date : 2018

Data Science On Google Cloud Platform Exploratory Data 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

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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

Advanced Applications Of Python Data Structures And Algorithms

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Author : Galety, Mohammad Gouse
language : en
Publisher: IGI Global
Release Date : 2023-07-05

Advanced Applications Of Python Data Structures And Algorithms written by Galety, Mohammad Gouse and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-05 with Computers categories.

Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.

Practical Applications Of Data Processing Algorithms And Modeling

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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.

Reproducible Data Science With Pachyderm

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Author : Svetlana Karslioglu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-18

Reproducible Data Science With Pachyderm written by Svetlana Karslioglu and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-18 with Computers categories.

Create scalable and reliable data pipelines easily with Pachyderm Key FeaturesLearn how to build an enterprise-level reproducible data science platform with PachydermDeploy Pachyderm on cloud platforms such as AWS EKS, Google Kubernetes Engine, and Microsoft Azure Kubernetes ServiceIntegrate Pachyderm with other data science tools, such as Pachyderm NotebooksBook Description Pachyderm is an open source project that enables data scientists to run reproducible data pipelines and scale them to an enterprise level. This book will teach you how to implement Pachyderm to create collaborative data science workflows and reproduce your ML experiments at scale. You'll begin your journey by exploring the importance of data reproducibility and comparing different data science platforms. Next, you'll explore how Pachyderm fits into the picture and its significance, followed by learning how to install Pachyderm locally on your computer or a cloud platform of your choice. You'll then discover the architectural components and Pachyderm's main pipeline principles and concepts. The book demonstrates how to use Pachyderm components to create your first data pipeline and advances to cover common operations involving data, such as uploading data to and from Pachyderm to create more complex pipelines. Based on what you've learned, you'll develop an end-to-end ML workflow, before trying out the hyperparameter tuning technique and the different supported Pachyderm language clients. Finally, you'll learn how to use a SaaS version of Pachyderm with Pachyderm Notebooks. By the end of this book, you will learn all aspects of running your data pipelines in Pachyderm and manage them on a day-to-day basis. What you will learnUnderstand the importance of reproducible data science for enterpriseExplore the basics of Pachyderm, such as commits and branchesUpload data to and from PachydermImplement common pipeline operations in PachydermCreate a real-life example of hyperparameter tuning in PachydermCombine Pachyderm with Pachyderm language clients in Python and GoWho this book is for This book is for new as well as experienced data scientists and machine learning engineers who want to build scalable infrastructures for their data science projects. Basic knowledge of Python programming and Kubernetes will be beneficial. Familiarity with Golang will be helpful.

Enterprise Applications Markets And Services In The Finance Industry

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Author : Jos van Hillegersberg
language : en
Publisher: Springer Nature
Release Date : 2023-04-29

Enterprise Applications Markets And Services In The Finance Industry written by Jos van Hillegersberg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-29 with Computers categories.

This book constitutes revised selected papers from the 11th International Workshop on Enterprise Applications, Markets and Services in the Finance Industry, FinanceCom 2022, held in Twente, The Netherlands, in August 2022. The 8 full papers presented in this volume were carefully reviewed and selected from a total of 25 submissions. They deal with the adoption of innovative technologies in the financial services industry. The conference features four main themes: networks and business models, financial markets, IT and implementations, and new emerging digital and virtual financial markets.

Ace The Google Machine Learning Engineer Certification

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Author : Etienne Noumen
language : en
Publisher: Etienne Noumen
Release Date :

Ace The Google Machine Learning Engineer Certification written by Etienne Noumen and has been published by Etienne Noumen this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

Master Google Cloud’s most advanced AI certification with this definitive 2025 study guide. From TensorFlow and data pipelines to ML ops, model deployment, and ethical AI—this book delivers the knowledge, tools, and confidence to help you ace the Professional Machine Learning Engineer Exam. Backed by real-world examples, mock exams, and hands-on insights. 🎯 The ins and outs of Google's Machine Learning Engineer certification are explored in detail. A comprehensive guide is provided, covering the latest updates and offering tips for success. Why This Certification Matters - The growing demand for skilled Machine Learning Engineers - Career advancement and increased earning potential - The Google brand and its weight in the tech world Decoding the Certification: Requirements & Exam Structure - The four main exam domains: Machine Learning Concepts, Data Analysis, Model Building and Evaluation, and Machine Learning Systems Design - Exam format and structure: Multiple-choice, coding, and open-ended questions - The Google Cloud Platform (GCP) proficiency requiredMastering the Material: Essential Skills & Resources - Key concepts: Supervised and unsupervised learning, deep learning, natural language processing, computer vision - Recommended resources: Coursera, Udacity, Google Cloud Skills Boost, and relevant online communities - Practical projects: Building your own portfolio to showcase your skills Strategies for Success: Effective Preparation & Exam Day Tips - Practice, practice, practice: Using mock exams, coding exercises, and real-world datasets - Time management: Balancing learning, practice, and exam-day strategy - Stress management: Techniques to stay calm and focused on exam day Full Practice Exam - 2025 included Beyond the Certification: Career Paths & Continued Learning - The book explores potential roles: Machine Learning Engineer, Data Scientist, AI Researcher - The importance of continuous learning and staying updated with advancements in the field - Building your professional network and actively contributing to the ML community 📘 Download the E-Book + Audiobook combo at Djamgatech at https://djamgatech.com/product/ace-the-google-machine-learning-engineer-certification-2025-update-e-book-audiobook/ 📘 You can also Download the E-Book + Audiobook combo at Google Play Books at https://play.google.com/store/audiobooks/details?id=AQAAAEDKqGjosM

Ultimate Enterprise Data Analysis And Forecasting Using Python Leverage Cloud Platforms With Azure Time Series Insights And Aws Forecast Components For Time Series Analysis And Forecasting With Deep Learning Modeling Using Python

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Author : Shanthababu Pandian
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2023-12-28

Ultimate Enterprise Data Analysis And Forecasting Using Python Leverage Cloud Platforms With Azure Time Series Insights And Aws Forecast Components For Time Series Analysis And Forecasting With Deep Learning Modeling Using Python written by Shanthababu Pandian and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-28 with Computers categories.

Practical Approaches to Time Series Analysis and Forecasting using Python for Informed Decision-Making Key Features ● Comprehensive Resource for Python-Based Time Series Analysis and Forecasting. ● Delve into real-world applications with industry-specific case studies. ● Extract valuable insights by solving time series challenges across various sectors. ● Understand the significance of Azure Time Series Insights and AWS Forecast components. ● Practical insights into leveraging cloud platforms for efficient time series forecasting. Book Description Embark on a transformative journey through the intricacies of time series analysis and forecasting with this comprehensive handbook. Beginning with the essential packages for data science and machine learning projects you will delve into Python's prowess for efficient time series data analysis, exploring the core components and real-world applications across various industries through compelling use-case studies. From understanding classical models like AR, MA, ARMA, and ARIMA to exploring advanced techniques such as exponential smoothing and ETS methods, this guide ensures a deep understanding of the subject. It will help you navigate the complexities of vector autoregression (VAR, VMA, VARMA) and elevate your skills with a deep dive into deep learning techniques for time series analysis. By the end of this book, you will be able to harness the capabilities of Azure Time Series Insights and explore the cutting-edge AWS Forecast components, unlocking the cloud's power for advanced and scalable time series forecasting. What you will learn ● Explore Time Series Data Analysis and Forecasting, covering components and significance. ● Gain a practical understanding through hands-on examples and real-world case studies. ● Master Time Series Models (AR, MA, ARMA, ARIMA, VAR, VMA, VARMA) with executable samples. ● Delve into Deep Learning for Time Series Analysis, demystified with classical examples. ● Actively engage with Azure Time Series Insights and AWS Forecast components for a contemporary perspective. Table of Contents 1. Introduction to Python and its key packages for DS and ML Projects 2. Python for Time Series Data Analysis 3. Time Series Analysis and its Components 4. Time Series Analysis and Forecasting Opportunities in Various Industries 5. Exploring various aspects of Time Series Analysis and Forecasting 6. Exploring Time Series Models - AR, MA, ARMA, and ARIMA 7. Understanding Exponential Smoothing and ETS Methods in TSA 8. Exploring Vector Autoregression and its Subsets (VAR, VMA, and VARMA) 9. Deep Learning for Time Series Analysis and Forecasting 10. Azure Time Series Insights 11. AWS Forecast Index

Foundations Of Data Science

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Author : Dr. M. Muthamizh Selvam
language : en
Publisher: RK Publication
Release Date : 2024-09-05

Foundations Of Data Science written by Dr. M. Muthamizh Selvam and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-05 with Computers categories.

Foundations of Data Science is a comprehensive guide that introduces key concepts and techniques essential for understanding and analyzing data in the modern world. Foundational topics like statistics, probability, linear algebra, and machine learning, offering practical insights and applications in real-world data science. With a focus on both theory and implementation, it is designed for students and professionals seeking to build a solid grounding in data science principles and develop skills in data-driven problem-solving, analysis, and predictive modeling across diverse domains.