Otros libros que te pueden interesar

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  A Guide to Data Science and...

  Lila Monroe

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  Are you prepared for a revolutionary journey into machine learning and data science? The book "A Guide to Data Science and Machine Learning: From Data to Insights—Exploring the Intersection of Data Science and Machine Learning" will assist you to understand the nuances of rapidly developing scientific disciplines. This book gives you a thorough guide to comprehending the constantly changing world of innovation and technology, regardless of your experience level. Whether you're a beginner looking for basic knowledge or an advanced practitioner looking to expand your knowledge. 
  Enter the core of data science and learn about the fundamental ideas behind collecting, cleaning, and preprocessing data. You will understand the importance of preparing data for analysis through interesting explanations and practical examples, which will pave the way for perceptive investigation. Discover the power of exploratory data analysis (EDA), which helps you make decisions by revealing patterns, anomalies, and hidden insights in datasets. 
  Develop your knowledge as you explore the complex realm of feature engineering and selection. Discover how to turn raw data into insightful features that may be used to improve performance and make more accurate predictions. Learn how to effectively express complicated ideas through visual representations and use data to inform decision-making by delving into the art of data visualization. 
  An unlimited source of knowledge and creativity is ahead, and "A Guide to Data Science and Machine Learning: From Data to Insights—Exploring the Intersection of Data Science and Machine Learning" is your road map. This book invites you to embrace the transformational power of data science and machine learning, whether you're a seasoned practitioner, a curious learner, or a budding enthusiast. Together, we'll embark on a journey that embraces curiosity, interest, and the limitless potential of human intellect.

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  Touchpad Plus Ver 40 Class 7

  Nidhi Gupta

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  Computer Science Textbook with New Pedagogical Approaches 
  
  KEY FEATURES 
  - National Education Policy 2020 
  - Tech Funda: This section provides a practical information or tip to the students. 
  - Clickipedia: This section provides interesting computer facts. 
  - Lab Session: This is a lab activity to develop practical skills. (Subject Enrichment) 
  - Explore More: This section contains supplement topics for add-on knowledge. 
  - QR Code: Scan the QR Code given on the first page of each chapter to start chapter animation. 
  - Mind Boggler: This section has puzzle or fun based activity to help understand the concepts better. 
  
  DESCRIPTION 
  Computer technology has become essential and an integral part of life at work, in recreation, social networking and education too. With the constant development of new technology, it has become more significant in helping and preparing students for jobs. Computers have revolutionised the way education is imparted to children. 
  
  Touchpad Plus Version 4.0 is a complete computer science curriculum solution for grades 1-8. It is based on Windows 10 and MS Office 2019, with new and future-ready content. Fun is the most important element of learning. Keeping in mind the concept of Joyful Learning, varied activities have been designed based on multiple intelligences and 21st century skills for holistic development. 
  
  The books have a conversational style introduction of each chapter to make learning fun and engaging. The topics and their approaches are integrated in different themes as per ICT learning. Grade I and II books have four-line writing space to enhance writing skills in children. Each book is accompanied by digital learning resources that offer interesting animation and interactive tests for the student to supplement classroom learning with independent learning. 
  
  The books are curated in a way that they make students and teachers equal partners in the learning process and take learning beyond classroom. We welcome and look forward to all meaningful and valuable suggestions for improving the book 
  
  WHAT WILL YOU LEARN 
  You will learn about: 
  - Digital World 
  - Cyber World 
  - Coding World 
  - Computational Thinking 
  - Artificial Intelligence 
  
  WHO THIS BOOK IS FOR 
  Grade 7 
  
  TABLE OF CONTENTS 
  1. Number System 
  2. Advanced Features of Excel 
  3. Layers in Krita 
  4. Animations in Krita 
  5. Google Apps 
  6. App Development 
  7. More on HTML5 
  8. Lists and Tables in HTML5 
  9. Algorithmic Intelligence 
  10. Conditional Statements in Python 
  11. Concept of Smart Living 
  ADD-ONS 
  ASSESSMENTS

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  The Software Engineer's...

  Gergely Orosz

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  In my first few years as a developer I assumed that hard work was all I needed. Then I was passed over for a promotion and my manager couldn’t give me feedback on what areas to improve, so I could get to the senior engineer level. I was frustrated; even bitter: not as much about missing the promotion, but because of the lack of guidance. 
  By the time I became a manager, I was determined to support engineers reporting to me with the kind of feedback and support I wish I would have gotten years earlier. And I did. While my team tripled over the next two years, people became visibly better engineers, and this progression was clear from performance reviews and promotions. 
  This book is a summary of the advice I’ve given to software engineers over the years – and then some more. 
  This book follows the structure of a “typical” career path for a software engineer, from starting out as a fresh-faced software developer, through being a role model senior/lead, all the way to the staff/principle/distinguished level. It summarizes what I’ve learned as a developer and how I’ve approached coaching engineers at different stages of their careers. 
  We cover “soft” skills which become increasingly important as your seniority increases, and the “hard” parts of the job, like software engineering concepts and approaches which help you grow professionally. 
  Praise for the book 
  “From performance reviews to P95 latency, from team dynamics to testing, Gergely demystifies all aspects of a software career. This book is well named: it really does feel like the missing guidebook for the whole industry.” – Tanya Reilly, principal engineer and author of The Staff Engineer's Path 
  "Spanning a huge range of topics from technical to social in a concise manner, this belongs on the desk of any software engineer looking to grow their impact and their career." – James Stanier, Director of Engineering at Shopify

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  How to Land Your Dream Dental...

  Dr. Tony Schicktanz DDS

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  Mastering Your Dental Career: A Guide for New Dentists Navigating Life After Graduation 
  Graduating from dental school is just the beginning of your journey—but what comes next? Dr. Tony Schicktanz, a licensed dentist practicing in New Mexico and Arizona, offers the ultimate guide for new dentists ready to navigate the transition from student to professional. 
  From choosing between private practice and corporate dentistry to securing the perfect associateship, this book covers everything you need to successfully launch your career. You’ll gain valuable advice on how to:Make informed decisions about your career path.Find and secure your dream dental associateship.Review and negotiate associate agreements with confidence.Avoid costly mistakes by reviewing the red flags document 
  Packed with practical tips and straightforward advice, this is an essential resource for new dentists looking to take control of their professional future. Whether you’re unsure of your next steps or eager to land the perfect role, this guide will help you build the career of your dreams. 
  “As always, stay drilling, my friends!” – Dr. Tony Schicktanz

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  Bioplastics from Waste - The...

  Carlos Enrique Montenegro Marín,...

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  Los polihidroxialcanoatos (PHA) son polímeros biodegradables con propiedades similares a los plásticos convencionales, que ofrecen una alternativa sostenible y valorizan los residuos de lodos de depuradora. Su principal desafío de producción es el alto costo. Esta revisión, basada en la metodología PRISMA, se centra en el uso de cultivos microbianos mixtos y materias primas renovables (principalmente, ácidos grasos volátiles de lodos) para viabilizar la producción de PHA. El libro sintetiza investigaciones sobre sustratos, la estrategia de alimentación dinámica aerobia para enriquecer biomasa, condiciones operativas y rendimientos reportados. También se describe el proceso desde la obtención del sustrato hasta la producción del polímero, y se destaca la necesidad de optimizar condiciones para escalar esta prometedora tecnología de base biológica.

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  Machine Learning

  Chuck Sherman

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  "Machine Learning” In this captivating exploration, you'll traverse the ever-expanding realm of artificial intelligence and machine learning, guided by a comprehensive and insightful narrative. 
  From its origins in the visionary minds of early computer scientists to its current status as a driving force behind technological innovation, machine learning's evolution is vividly brought to life. Delve into the heart of supervised learning algorithms, where linear regression, logistic regression, decision trees, support vector machines, and neural networks form the bedrock of predictive analytics. 
  Venturing deeper, the book unravels the mysteries of unsupervised learning, illuminating clustering techniques, dimensionality reduction, and the crucial task of anomaly detection. With clarity and precision, it demystifies the captivating world of reinforcement learning, painting a vivid picture of agents learning to navigate and excel within complex environments. 
  The journey wouldn't be complete without the profound influence of deep learning and neural networks. Traverse the landscapes of multilayer perceptrons, convolutional neural networks, recurrent neural networks, and generative adversarial networks, witnessing the power of AI to understand and create. 
  However, the book doesn't shy away from critical considerations. Ethical and responsible AI practices take center stage, addressing bias, fairness, explainability, and data privacy to ensure that machine learning remains a force for good. Practical wisdom awaits too, as the reader is led through a comprehensive machine learning workflow – from data collection to model deployment. 
  As the final chapters unfold, the horizon broadens to reveal the future frontiers of machine learning. Quantum machine learning and federated learning beckon as game-changers, and applications across domains like healthcare, finance, and more stand poised to revolutionize the world as we know it.

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