Tabla de Contenidos: “…-- BI roles -- Problem solving -- Specific industry knowledge and subject matter expertise -- Communication skills -- Statistical analysis -- Technical knowledge -- Business acumen -- Keep up with innovation -- Potential entrances to the BI world -- BI roadmap -- ETL developers -- Data architects -- Data modelers -- BI developers -- Data scientists -- Technology solutions stack -- Non-technical data analysis -- Case 1 -- Case 2 -- Case 3 -- Case 4 -- Case 5 -- Summary -- Chapter 2: How to Become Proficient in Analyzing Data -- Building a taxonomy of your data sources -- How to use a BI tool to explore data -- Understanding your data needs -- Summary -- Chapter 3: How to Talk Data -- Presenting data -- Know your audience -- Choose the right visualization -- Keep it simple -- Use color and formatting effectively -- Provide context -- Tell a story -- High-level dashboards -- Operational reports -- Talking to stakeholders -- Data visualization taxonomy -- Bar charts -- Line charts -- Pie charts -- Scatter plots -- Area charts -- Heat maps -- Bubble charts -- Gauge charts -- Tree maps -- Box plots -- Advanced data visualizations -- Sankey diagrams -- Bullet charts -- Taxonomy diagrams -- Pareto diagrams -- Decision tree for picking a visualization -- Storytelling -- Summary -- Chapter 4: How To Crack the BI Interview Process -- Finding the right interview -- Building a business problem and data solutions matrix -- Potential business cases and solutions -- Teamwork -- Customer service -- Adaptability -- Time management -- Communication -- Motivation and values -- A hypothetical BI interview process and what to expect -- General business intelligence interview questions -- Scenario-based BI questions…”

Tabla de Contenidos: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Foolish Assumptions -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Getting Started with Data Science and Python -- Chapter 1 Discovering the Match between Data Science and Python -- Defining the Sexiest Job of the 21st Century -- Considering the emergence of data science -- Outlining the core competencies of a data scientist -- Linking data science, big data, and AI -- Understanding the role of programming -- Creating the Data Science Pipeline -- Preparing the data -- Performing exploratory data analysis -- Learning from data -- Visualizing -- Obtaining insights and data products -- Understanding Python's Role in Data Science -- Considering the shifting profile of data scientists -- Working with a multipurpose, simple, and efficient language -- Learning to Use Python Fast -- Loading data -- Training a model -- Viewing a result -- Chapter 2 Introducing Python's Capabilities and Wonders -- Why Python? …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- Acknowledgments -- About the Author -- About the Technical Editor -- Contents -- Introduction -- How This Book Is Organized -- Who Should Read This Book? -- Data Scientists and AI Teams -- IT Leaders and Teams -- Students and Academia -- Consultants and Advisors -- Business Strategists and Leaders -- C-Level Executives -- Why You Should Read This Book -- Unique Features -- Comprehensive Coverage of All Aspects of Enterprise-wide AI Transformation -- Case Study Approach -- Coverage of All Major Cloud Platforms -- Discussion of Nontechnical Aspects of AI -- Best Practices for MLOps and AI Governance -- Up-to-Date Content -- Hands-on Approach -- Part I Introduction -- Chapter 1 Enterprise Transformation with AI in the Cloud -- Understanding Enterprise AI Transformation -- Why Some Companies Succeed at Implementing AI and ML While Others Fail -- Transform Your Company by Integrating AI, ML and Gen AI into Your Business Processes -- Adopt AI-First to Become World-Class -- Importance of an AI-First Strategy -- Prioritize AI and Data Initiatives -- Leveraging Enterprise AI Opportunities -- Enable One-to-One, Personalized, Real-Time Service for Customers at Scale -- Enterprise-wide AI Opportunities -- Growing Industry Adoption of AI -- Workbook Template - Enterprise AI Transformation Checklist -- Summary -- Review Questions -- Answer Key -- Chapter 2 Case Studies of Enterprise AI in the Cloud -- Case Study 1: The U.S. …”

Tabla de Contenidos: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Foolish Assumptions -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Getting Started with Data Science and Python -- Chapter 1 Discovering the Match between Data Science and Python -- Understanding Python as a Language -- Viewing Python's various uses as a general-purpose language -- Interpreting Python -- Compiling Python -- Defining Data Science -- Considering the emergence of data science -- Outlining the core competencies of a data scientist -- Linking data science, big data, and AI -- Creating the Data Science Pipeline -- Understanding Python's Role in Data Science -- Considering the shifting profile of data scientists -- Working with a multipurpose, simple, and efficient language -- Learning to Use Python Fast -- Loading data -- Training a model -- Viewing a result -- Chapter 2 Introducing Python's Capabilities and Wonders -- Working with Python -- Contributing to data science -- Getting a taste of the language -- Understanding the need for indentation -- Working with Jupyter Notebook and Google Colab -- Performing Rapid Prototyping and Experimentation -- Considering Speed of Execution -- Visualizing Power -- Using the Python Ecosystem for Data Science -- Accessing scientific tools using SciPy -- Performing fundamental scientific computing using NumPy -- Performing data analysis using pandas -- Implementing machine learning using Scikit-learn -- Going for deep learning with Keras and TensorFlow -- Performing analysis efficiently using XGBoost -- Plotting the data using Matplotlib -- Creating graphs with NetworkX -- Chapter 3 Setting Up Python for Data Science -- Working with Anaconda -- Using Jupyter Notebook -- Accessing the Anaconda Prompt -- Installing Anaconda on Windows -- Installing Anaconda on Linux…”

Texto completo en Odilo

“…Written and edited by a world leading scientist in the area of bioenergy and bioproducts Includes both principles and recent developments within bioenergy technologies Covers the fundamentals of the technologies and recent reviews…”

“…Welcome to Scientific Python and its community. If you’re a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. …”

“…Whether you are a developer, engineer, or scientist, if you are interested in exploring the power of OpenGL for data visualization, this book is for you. …”

“…Gain sharp insights into your data and solve real-world data science problems with R-from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. …”

“…Get a fundamental understanding of how Google BigQuery works by analyzing and querying large datasets About This Book Get started with BigQuery API and write custom applications using it Learn how BigQuery API can be used for storing, managing, and query massive datasets with ease A practical guide with examples and use-cases to teach you everything you need to know about Google BigQuery Who This Book Is For If you are a developer, data analyst, or a data scientist looking to run complex queries over thousands of records in seconds, this book will help you. …”

Tabla de Contenidos: “…System 2 Thinking -- An AI Scientist's Epiphany: Envisioning a HASI Future -- Hybrid AI: Potential Pathway to HASI -- Why Hybrid AI? …”

Tabla de Contenidos: “…-- Chapter 13: Make Friends -- True Friendship Never Dies -- Avoid Negative Friends -- A Tale on Friendship -- Tips to Make Friends -- Thoughts from Dale Carnegie's Book -- Chapter 14: Gel Well with Others -- Case Study of Robert -- Tips to Gel Well with Others -- Chapter 15: Manage Your Stress -- The Effects of Stress -- Tips to Manage Stress -- Chapter 16: Use Technology Wisely -- The Past Versus the Present -- Technology and the Youth -- Is Technology a Boon or a Bane? -- Technology and Scientists -- Technology in Movies -- Chapter 17: Take Care of Your Health -- Youth and Health -- Avoid Excess Fat -- Tips for Good Health -- A Healthy Mind in a Healthy Body -- Chapter 18: Motivate Yourself -- What is Motivation? …”

Tabla de Contenidos: “…PERSONNEL REQUIRED FOR BIOTECHNOLOGY -- Demand for Scientists -- Demographic Trends -- EDUCATION AND TRAINING -- Programs at the U.S. …”

Tabla de Contenidos: “…Aczel ; Turning students into citizen scientists / John Harlin, Laure Kloetzer, Dan Patton, Chris Leonhard and Leysin American School high school students ; Citizen science and the role of natural history museums / Andrea Sforzi, John Tweddle, Johannes Vogel, Grégoire Lois, Wolfgang Wägele, Poppy Lakeman-Fraser, Zen Makuch and Katrin Vohland ; Stories can change the world : citizen science communication in practice / Susanne Hecker, Monique Luckas, Miriam Brandt, Heidy Kikillus, Ilona Marenbach, Bernard Schiele, Andrea Sieber, Arnold J.H. van Vliet, Ulrich Walz and Wolfgang Wende -- Conclusions. …”

Tabla de Contenidos: “…-- The Evolution of OCM -- The Drivers of Change -- The Audio Technician -- The Success Rate of Organizational Change Projects -- Six Change Areas -- Connecting the Change Areas -- Recognizing Who Is Responsible -- Recurring Challenges in Change Management -- Change Fatigue or Continuous Change -- Reinforcing Change -- Implementing Change -- Making Time for Reflection -- Prioritizing Change Management -- Balancing Short-Term and Long-Term Change -- Conclusion -- Chapter 2 Think Like a Behavioral Scientist -- A Brief History of Behavioral Science -- The 1950s to 1970s: The Academic Foundation -- The 1980s to 1990s: The Early Years -- The 2000s: Going Mainstream -- The 2010s: Integration into Business Practices -- The 2020s: The Era of Behavioral Science -- BeSci Explained -- Use Cases of BeSci -- Business Strategy -- Marketing and Consumer Behavior -- Product Design and User Experience -- Finance and Risk Management -- Human Resources -- Organizational Change -- Mindset: BeSci as a Lens -- Bounded Rationality and Dual Processing Theories -- Cognitive Biases…”

Tabla de Contenidos: “…A Legislative Victory -- A Decentralized Bank -- Research Scientists Embrace Consulting -- Chapter 10 A Cautionary Tale: Trying on Yesterday's Methodologies -- A Brief History -- Today's Reality -- Consulting Methodology in Today's World -- Consultant as Perturber -- Purpose of an Intervention -- The Alignment Model -- Chapter 11 Change Is in the Details -- The Angel in the Details -- Knowing a Good Question When You Hear One -- Chapter 12 Talk Is Walk: Language and Courage in Action -- Leadership Talk -- Anxiety and Courage -- Strength at the Broken Places -- The Constructive Uses of Anxiety -- Chapter 13 So, What's Working Here? …”

Tabla de Contenidos: “…. -- Characteristics of an Optimal Meat and Poultry Inspection Program -- A System of Traceback to Producers -- 1985 Report -- Use of Plant Personnel to Monitor Critical Control Points -- 1985 Report -- Use of Contemporary Technologic Expertise in Inspection Management -- 1985 Report -- Multitiered Levels of Inspection -- 1985 Report -- Analysis of the Utility of Each Inspection Procedure -- 1985 Report -- Develop a Data Base on Specific Causes of Condemnations -- 1985 Report -- Rapid Screening for Residues -- 1985 Report -- Protection of Consumers from Residues -- 1985 Report -- Hazard Analysis Critical Control Point (HACCP) Programs -- 1985 Report -- Documentation and Compliance Enforcement -- 1985 Report -- Enhanced Enforcement Capability -- 1985 Report -- Improve Technologic Base of FSIS -- 1985 Report -- Mandatory Continuing Education -- 1985 Report -- Involvement of Scientists in Policy Development -- 1985 Report -- Expert Advisory Panels -- 1985 Report -- Interagency Liaison -- 1985 Report -- Data and Information Analysis -- 1985 Report -- Implementation Timetable -- 1985 Report -- RECOMMENDATIONS IN POULTRY INSPECTION: THE BASIS FOR A RISK-ASSESSMENT APPROACH (NRC, 1987A) -- RECOMMENDATIONS -- General Recommendations -- 1987 Report -- 1987 Report -- 1987 Report -- 1987 Report -- Specific Recommendations -- 1987 Report -- 1987 Report -- 1987 Report -- 1987 Report -- 1987 Report -- CONCLUSIONS -- REFERENCES -- APPENDICIES -- Appendix A Proposed Rules -- Effect on Small Entities -- Paperwork Requirements -- Comments -- Background -- I. …”

“…Hundreds of scientists, professionals, and students has gathered to discuss, analyze, and express their opinions about current issues today. …”