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Diving Deeper into Data Analysis

Diving Deeper into Data Analysis PDF Author: Dr. Colin A. Ferreira
Publisher: iUniverse
ISBN: 1663219761
Category : Education
Languages : en
Pages : 62

Book Description
This textbook demystifies the complex Statistical calculations and difficulty in analyzing and interpreting assessment data by presenting simplified approaches for: • Understanding data types and using appropriate graphical and numerical forms to describe data. • Correctly reading and interpreting quantitative data and qualitative data presented in charts, tables, and graphs including pie charts, bar graphs, two-way tables, side-by-side bar graphs, segmented bar graphs, line graphs, histograms, dotplots, parallel boxplots, side-by-side stemplots, and scatter plots. • Correctly reading and interpreting quantitative data presented in numerical forms including mean, median, standard deviation, range, interquartile range, percentiles, quartiles, and standardized scores (z-scores). • Making data-driven decisions based on statistical calculations and interpretations. • Using the results of prudent data analysis to drive leadership and instruction. • Using the findings of extensive data analysis of assessment data to develop an innovative school improvement action plan.

Diving Deeper into Data Analysis

Diving Deeper into Data Analysis PDF Author: Dr. Colin A. Ferreira
Publisher: iUniverse
ISBN: 1663219761
Category : Education
Languages : en
Pages : 62

Book Description
This textbook demystifies the complex Statistical calculations and difficulty in analyzing and interpreting assessment data by presenting simplified approaches for: • Understanding data types and using appropriate graphical and numerical forms to describe data. • Correctly reading and interpreting quantitative data and qualitative data presented in charts, tables, and graphs including pie charts, bar graphs, two-way tables, side-by-side bar graphs, segmented bar graphs, line graphs, histograms, dotplots, parallel boxplots, side-by-side stemplots, and scatter plots. • Correctly reading and interpreting quantitative data presented in numerical forms including mean, median, standard deviation, range, interquartile range, percentiles, quartiles, and standardized scores (z-scores). • Making data-driven decisions based on statistical calculations and interpretations. • Using the results of prudent data analysis to drive leadership and instruction. • Using the findings of extensive data analysis of assessment data to develop an innovative school improvement action plan.

Diving Deeper into SCUBA... Science

Diving Deeper into SCUBA... Science PDF Author: Costantino Balestra
Publisher: Acrodacrolivres
ISBN: 2512007367
Category : Sports & Recreation
Languages : en
Pages : 273

Book Description
You will find in this book some valuable and reliable lessons about safe diving The editors of and authors of this book are a cadre of scientists and physicians with broad experience and knowledge of diving physiology and decompression theory. As is often the case, it requires a group effort to succeed in advancing practical knowledge. The colloquialism "the whole is greater than the sum of its parts" is often true and the PHYPODE Reasearch Group epitomizes this concept. By logically grouping the various elements of diving science and medicine with provocative "food for thought" sections, the text offers valuable lessons to those interested in the current state of diving. Despite nearly 170 years of reasearch, the fundamenal nature of decompression stress remains elusive. As is well outlined in this book, great advances have been made to the practical elements allowing for safe diving. Nonetheless, there are glaring voids of knowledge related to the nature of bubble nucleation, its consequences and methods to ameliorate risk. The synergy exhibited in this text not only provides a foundation for what is known, it offers a glimpse of where research is taking us. - Professor Stephen R. Thom, Dept. of Emergency Medicine, University of Maryland School of Medicine This is a book for all diving fans who want to discover their passion through a scientific approach. EXCERPT Decompression illnesses (DCI), or as they are called more scientifically: dysbaric disorders, represent a complex spectrum of pathophysiological conditions with a wide variety of signs and symptoms related to dissolved gas and its subsequent phase change.1, 2 Any significant organic or functional dysfunction in individuals who have recently been exposed to a reduction in environmental pressure (i.e., decompression) must be considered as possibly being caused by DCI until proven otherwise. However, apart from the more obvious acute manifestations of a single, sudden decompression, individuals who have experienced repetitive exposures (e.g. commercial or professional divers and active recreational divers) may also develop sub-acute or chronic manifestations, even if subtle and almost symptomless. ABOUT THE AUTHORS Dr. Costantino Balestra started to study neurophysiology of fatigue then started studies on environmental physiology issues. He teaches physiology, biostatistics, research methodology, as well as other subjects. He Is the Director of the Integrative Physiology Laboratory and a full time professor at the Haute Ecole Bruxelles-Brabant (Brussels). He is VP of DAN Europe for research and education, Immediate past President of the European Underwater and Baromedical Society. Peter Germonpré is the Medical Director of the Centre for Hyperbaric Oxygen Therapy of the Military Hospital Brussels, Belgium).

Data Science on AWS

Data Science on AWS PDF Author: Chris Fregly
Publisher: "O'Reilly Media, Inc."
ISBN: 1492079340
Category : Computers
Languages : en
Pages : 524

Book Description
With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

Data Analysis Foundations with Python

Data Analysis Foundations with Python PDF Author: Cuantum Technologies LLC
Publisher: Packt Publishing Ltd
ISBN: 1836209061
Category : Computers
Languages : en
Pages : 551

Book Description
Dive into data analysis with Python, starting from the basics to advanced techniques. This course covers Python programming, data manipulation with Pandas, data visualization, exploratory data analysis, and machine learning. Key Features From Python basics to advanced data analysis techniques. Apply your skills to practical scenarios through real-world case studies. Detailed projects and quizzes to help gain the necessary skills. Book DescriptionEmbark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently. Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling. To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.What you will learn Develop a strong foundation in Python for data analysis. Manipulate and analyze data using NumPy and Pandas. Create insightful data visualizations with Matplotlib and Seaborn. Understand and apply probability theory and hypothesis testing. Implement supervised and unsupervised machine learning algorithms. Execute real-world data analysis projects with confidence. Who this book is for This course adopts a hands-on approach, seamlessly blending theoretical lessons with practical exercises and real-world case studies. Practical exercises are designed to apply theoretical knowledge, providing learners with the opportunity to experiment and learn through doing. Real-world applications and examples are integrated throughout the course to contextualize concepts, making the learning process engaging, relevant, and effective. By the end of the course, students will have a thorough understanding of the subject matter and the ability to apply their knowledge in practical scenarios.

The Ultimate Guide to Snowpark

The Ultimate Guide to Snowpark PDF Author: Shankar Narayanan SGS
Publisher: Packt Publishing Ltd
ISBN: 1805124455
Category : Computers
Languages : en
Pages : 254

Book Description
Develop robust data pipelines, deploy mature machine learning models, and build secure data apps with Snowpark using Python Key Features Get to grips with Snowpark’s basic and advanced features Implement workloads in domains like data engineering, data science, and data applications using Snowpark with Python Deploy Snowpark in production with practical examples and best practices Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionSnowpark is a powerful framework that helps you unlock numerous possibilities within the Snowflake Data Cloud. However, without proper guidance, leveraging the full potential of Snowpark with Python can be challenging. Packed with practical examples and code snippets, this book will be your go-to guide to using Snowpark with Python successfully. The Ultimate Guide to Snowpark helps you develop an understanding of Snowpark and how it enables you to implement workloads in data engineering, data science, and data applications within the Data Cloud. From configuration and coding styles to workloads such as data manipulation, collection, preparation, transformation, aggregation, and analysis, this guide will equip you with the right knowledge to make the most of this framework. You'll discover how to build, test, and deploy data pipelines and data science models. As you progress, you’ll deploy data applications natively in Snowflake and operate large language models (LLMs) using Snowpark container services. By the end of this book, you'll be able to leverage Snowpark's capabilities and propel your career as a Snowflake developer to new heights.What you will learn Harness Snowpark with Python for diverse workloads Develop robust data pipelines with Snowpark using Python Deploy mature machine learning models Explore the process of developing, deploying, and monetizing native apps using Snowpark Deploy and operate containers in Snowpark Discover the pathway to adopting Snowpark effectively in production Who this book is for This book is for data engineers, data scientists, developers, and data practitioners seeking an in-depth understanding of Snowpark’s features and best practices for deploying various workloads in Snowpark using the Python programming language. Basic knowledge of SQL, proficiency in Python, an understanding of data engineering and data science basics, and familiarity with the Snowflake Data Cloud platform are required to get the most out of this book.

Practical Data Analytics for BFSI

Practical Data Analytics for BFSI PDF Author: Bharat Sikka
Publisher: Orange Education Pvt Ltd
ISBN: 9388590902
Category : Computers
Languages : en
Pages : 356

Book Description
Revolutionizing BFSI with Data Analytics KEY FEATURES ● Real-world examples and exercises will ground you in the practical application of analytics techniques specific to BFSI. ● Master Python for essential coding, SQL for data manipulation, and industry-leading tools like IBM SPSS and Power BI for sophisticated analyses. ● Understand how data-driven strategies generate profits, mitigate risks, and redefine customer support dynamics within the BFSI sphere. DESCRIPTION Are you looking to unlock the transformative potential of data analytics in the dynamic world of Banking, Financial Services, and Insurance (BFSI)? This book is your essential guide to mastering the intricate interplay of data science and analytics that underpins the BFSI landscape. Designed for intermediate-level practitioners, as well as those aspiring to join the ranks of BFSI analytics professionals, this book is your compass in the data-driven realm of banking. Address the unique challenges and opportunities of the BFSI sector using Artificial Intelligence and Machine Learning models for a data driven analysis. This book is a step by step guide to utilize tools like IBM SPSS and Microsoft Power BI. Hands-on examples that utilize Python and SQL programming languages make this an essential guide. The book features numerous case studies that illuminate various use cases of Analytics in BFSI. Each chapter is enriched with practical insights and concludes with a valuable multiple-choice questionnaire, reinforcing understanding and engagement. This book will uncover how these solutions not only pave the way for increased profitability but also navigate risks with precision and elevate customer support to unparalleled heights. WHAT WILL YOU LEARN ● Delve into the world of Data Science, including Artificial Intelligence and Machine Learning, with a focus on their application within BFSI. ● Explore hands-on examples and step-by-step tutorials that provide practical solutions to real-world challenges faced by banking institutions. ● Develop skills in essential programming languages such as Python (fundamentals) and SQL (intermediate), crucial for effective data manipulation and analysis. ● Gain insights into how businesses adapt data-driven strategies to make informed decisions, leading to improved operational efficiency. ● Stay updated on emerging trends, technologies, and innovations shaping the future of data analytics in the BFSI industry. WHO IS THIS BOOK FOR? This book is tailored for professionals already engaged in or seeking roles within Data Analytics in the BFSI industry. Additionally, it serves as a strategic resource for business leaders and upper management, guiding them in shaping data platforms and products within their organizations. The book also serves as a starting point for individuals interested in the BFSI sector. Prior experience with coding tools such as Python, SQL, Power BI is beneficial but not required as it covers all dimensions from the basics. TABLE OF CONTENTS 1. Introduction to BFSI and Data Driven Banking 2. Introduction to Analytics and Data Science 3. Major Areas of Analytics Utilization 4. Understanding Infrastructures behind BFSI for Analytics 5. Data Governance and AI/ML Model Governance in BFSI 6. Domains of BFSI and team planning 7. Customer Demographic Analysis and Customer Segmentation 8. Text Mining and Social Media Analytics 9. Lead Generation Through Analytical Reasoning and Machine Learning 10. Cross Sell and Up Sell of Products through Machine Learning 11. Pricing Optimization 12. Data Envelopment Analysis 13. ATM Cash Forecasting 14. Unstructured Data Analytics 15. Fraud Modelling 16. Detection of Money Laundering and Analysis 17. Credit Risk and Stressed Assets 18. High Performance Architectures: On-Premises and Cloud 19. Growing Trends in the Data-Driven Future of BFSI

From Zero to Data Hero with ChatGPT

From Zero to Data Hero with ChatGPT PDF Author: Andrew Wu
Publisher: Andrew Wu
ISBN:
Category : Computers
Languages : en
Pages : 230

Book Description
This is a comprehensive guide for prospective data scientists. It combines practical skills and advanced techniques with ChatGPT's groundbreaking capabilities. This easy-to-follow book shortens the learning curve for data analysis and machine learning beginners. It includes five chapters: 1. Kickstart Your Data Science Journey with ChatGPT's Power Tools: Introduces ChatGPT and the Noteable Plugin for quick data analysis. 2. The Great Data Hunt: Data collection and manipulation, including APIs, web scraping, data formats. 3. Making Data Meaningful: The basics of data analysis, simplified statistics and practical exercises. 4. Seeing the Unseen: Data Visualization: Techniques for revealing patterns in data using visual tools. 5. Venturing into the Machine's Mind: Machine Learning: Demystifies machine learning from regression analysis to recommendation engines, utilizing ChatGPT. Perfect for students, professionals and enthusiasts alike, this book offers a groundbreaking approach that makes data science accessible and manageable with the help of ChatGPT.

Data Analytics Essentials You Always Wanted To Know

Data Analytics Essentials You Always Wanted To Know PDF Author: Vibrant Publishers
Publisher: Vibrant Publishers
ISBN: 1636511198
Category : Business & Economics
Languages : en
Pages : 170

Book Description
Upon reading this book, you will get:  A fundamental comprehension of data analytics, including its types  An understanding of data analytics processes, software tools, and a range of analytics methodologies  A comprehension of what daily tasks and procedures the data analysts follow  An investigation into the vast field of big data analytics, covering its possibilities and challenges  An understanding of the existing legal frameworks, as well as ethical and privacy issues in data analytics  Application-based learning using a variety of real-world case studies From raw data to actionable insights - journey through the essentials of data analytics. Data Analytics Essentials You Always Wanted To Know is an approachable and captivating guide to understand the complicated world of data Data analytics is becoming increasingly important in today's data-driven society, and so has the demand for data analysts. Data Analytics Essentials You Always Wanted to Know (Data Analytics Essentials) is a comprehensive yet succinct manual, perfect for you if you are trying to understand the fundamentals of data analytics. It gives a concise introduction to data analytics and its current applicability. This book is a great tool for professionals switching to a career in data analytics and for students who want to learn the basics of data analytics. It will give you a strong foundation by explaining everything in an easy-to-understand language. Data Analytics Essentials goes beyond a theoretical manual and contains real-world case studies and fun facts to help you enhance your knowledge. The chapter summaries and self- assessment tests along with every chapter will help you test yourself as you move from one concept to the next.

Big Data Analysis with Python

Big Data Analysis with Python PDF Author: Ivan Marin
Publisher: Packt Publishing Ltd
ISBN: 1789950732
Category : Computers
Languages : en
Pages : 276

Book Description
Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python. Key FeaturesGet a hands-on, fast-paced introduction to the Python data science stackExplore ways to create useful metrics and statistics from large datasetsCreate detailed analysis reports with real-world dataBook Description Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems. The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools. By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs. What you will learnUse Python to read and transform data into different formatsGenerate basic statistics and metrics using data on diskWork with computing tasks distributed over a clusterConvert data from various sources into storage or querying formatsPrepare data for statistical analysis, visualization, and machine learningPresent data in the form of effective visualsWho this book is for Big Data Analysis with Python is designed for Python developers, data analysts, and data scientists who want to get hands-on with methods to control data and transform it into impactful insights. Basic knowledge of statistical measurements and relational databases will help you to understand various concepts explained in this book.

AI-Aided IoT Technologies and Applications for Smart Business and Production

AI-Aided IoT Technologies and Applications for Smart Business and Production PDF Author: Alex Khang
Publisher: CRC Press
ISBN: 1003821510
Category : Computers
Languages : en
Pages : 312

Book Description
This book covers the need for Internet of Things (IoT) technologies and artificial intelligence (AI)–aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. AI-Aided IoT Technologies and Applications for Smart Business and Production shows how a variety of IoT technologies can be used toward integrating data fabric solutions and how intelligent applications can be used to greater effect in business and production operations. The book also covers the integration of IoT data-driven financial technology (fintech) applications to fulfill the goals of trusted AI-aided IoT solutions. Next, the authors show how IoT-based technology uses algorithms and AI models to bring out the desired results across various industries including smart cities, buildings, hospitals, hotels, homes, factories, agriculture, transportation, and more. The last part focuses on AI-aided IoT techniques, data analytics, and visualization tools. This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, and professionals. It will be useful to engineering officers, IoT and AI engineers, engineering and industrial management students, and research scholars looking for new ideas, methodologies, technologies, models, frameworks, theories, and practices to resolve the challenging issues associated with leveraging IoT technologies, data-driven analytics, AI-aided models, IoT cybersecurity, 5G, sensors, and augmented and virtual reality techniques for developing smart systems in the era of Industrial Revolution 4.0.