Download or read book Learn To Model written by Bob Pardue and published by Lulu.com. This book was released on 2012-02-23 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has more than 80 Pages with Six Chapters of Pure Tips, Tricks, Hints and Instructions with Valuable Information. Learning on how to become a model is no Joke, with lack of information everywhere and schools charging anywhere from $1000 or more how is anyone supposed to become and succeed as a model. You can go to Amazon, Barns and Nobles or any Book Store online and you will find books on how to become a model. However, this one is written from a professional modeling photographer's point of view giving you a new perspective. After years of experience and giving advice people have been asking me when am I going to write a book. Here it is, The moment you have been waiting for. Read This Book before paying or hiring any school or photographer to be ahead in the game and you'll be glad you did. Improve your chances and get all the information you need to become a high paying field in modeling and succeed as a high paying model.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book The Model Thinker written by Scott E. Page and published by Basic Books. This book was released on 2018-11-27 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja. From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Download or read book I Want to Model written by Nia Burnett and published by . This book was released on 2018-10-08 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to learn how to be a professional model, but are new to the modeling industry, and you are looking for help building your modeling career, then this ebook was created for you in mind. There is always someone who wants to be the next Tyra Banks ,Kendall Jenner, or Ashley Graham but despite what the movies tell us, becoming a model isn't just about having really good looks. It's about having the uniqueness, talent and drive to back up those assets. Let this book guide you and teach you the do's and don't of this industry and how you can avoid pitfalls. In this ebook, we will give you all the necessary information on how to get started in the modeling industry. You will learn how tofigure out your market, how to pose, how to get signed to an agency, to work with casting agents and photographers, and many more! Here is a preview of what you will learn: Finding your market depending on your size and body type, Building your portfolio, Posing skills, How to go on castings and go-see's, Do's & Don'ts of the audition process, How to choose the right modeling agency, Understanding modeling contracts, How to get paid as a model, How to stay Successful, How to brand yourself, And much much more...Download your copy today!
Download or read book A Beginner s Guide to 3D Modeling written by Cameron Coward and published by No Starch Press. This book was released on 2019-06-11 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Beginner’s Guide to 3D Modeling is a project-based, straightforward introduction to computer-aided design (CAD). You’ll learn how to use Autodesk Fusion 360, the world’s most powerful free CAD software, to model gadgets, 3D print your designs, and create realistic images just like an engineering professional—with no experience required! Hands-on modeling projects and step-by-step instructions throughout the book introduce fundamental 3D modeling concepts. As you work through the projects, you’ll master the basics of parametric modeling and learn how to create your own models, from simple shapes to multipart assemblies. Once you’ve mastered the basics, you’ll learn more advanced modeling concepts like sweeps, lofts, surfaces, and rendering, before pulling it all together to create a robotic arm. You’ll learn how to: • Design a moving robotic arm, a door hinge, a teapot, and a 20-sided die • Create professional technical drawings for manufacturing and patent applications • Model springs and other complex curves to create realistic designs • Use basic Fusion 360 tools like Extrude, Revolve, and Hole • Master advanced tools like Coil and Thread Whether you’re a maker, hobbyist, or artist, A Beginner’s Guide to 3D Modeling is certain to show you how to turn your ideas into professional models. Go ahead—dust off that 3D printer and feed it your amazing designs.
Download or read book Ready to Learn written by Peggy J. Grafwallner and published by . This book was released on 2019 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In F.R.A.M.E.: How to F.R.A.M.E. (Focus, Reach, Achieve, Model, and Encourage) Your Class for Optimum Learning, author Peg Grafwallner emphasizes the importance of designing and delivering lessons that create a motivating and engaging learning experience for all students. This book describes the FRAME protocol, a five-step model educators can use to combat student boredom and create classroom communities, structured for optimal learning. The protocol's five steps--(1) focus, (2) reach, (3) ask and analyze, (4) model and instruct, and (5) encourage--support teachers in launching engaging lessons, articulating clear expectations, and offering meaningful feedback. By reading F.R.A.M.E., K-12 teachers will receive the tools and strategies needed to support effective learning for all students across all grade levels and content areas"--
Download or read book Motivational Design for Learning and Performance written by John M. Keller and published by Springer Science & Business Media. This book was released on 2009-11-24 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is impossible to control another person’s motivation. But much of the instructor’s job involves stimulating learner motivation, and learning environments should ideally be designed toward this goal. Motivational Design for Learning and Performance introduces readers to the core concepts of motivation and motivational design and applies this knowledge to the design process in a systematic step-by-step format. The ARCS model—theoretically robust, rooted in best practices, and adaptable to a variety of practical uses—forms the basis of this problem-solving approach. Separate chapters cover each component of the model—attention, relevance, confidence, and satisfaction—and offer strategies for promoting each one in learners. From there, the motivational design process is explained in detail, supplemented by real-world examples and ready-to-use worksheets. The methods are applied to traditional and alternative settings, including gifted classes, elementary grades, self-directed learning, and corporate training. And the book is geared toward the non-specialist reader, making it accessible to those without a psychology or teaching background. With this guide, the reader learns how to: Identify motivation problems and goals Decide whether the environment or the learners need changing Generate attention, relevance, confidence, and satisfaction in learners Integrate motivational design and instructional design Select, develop, and evaluate motivational materials Plus a wealth of tables, worksheets, measures, and other valuable tools aid in the design process Comprehensive and enlightening, Motivational Design for Learning and Performance furnishes an eminently practical body of knowledge to researchers and professionals in performance technology and instructional design as well as educational psychologists, teachers and trainers.
Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Download or read book Modelling Learners and Learning in Science Education written by Keith S. Taber and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sets out the necessary processes and challenges involved in modeling student thinking, understanding and learning. The chapters look at the centrality of models for knowledge claims in science education and explore the modeling of mental processes, knowledge, cognitive development and conceptual learning. The conclusion outlines significant implications for science teachers and those researching in this field. This highly useful work provides models of scientific thinking from different field and analyses the processes by which we can arrive at claims about the minds of others. The author highlights the logical impossibility of ever knowing for sure what someone else knows, understands or thinks, and makes the case that researchers in science education need to be much more explicit about the extent to which research onto learners’ ideas in science is necessarily a process of developing models. Through this book we learn that research reports should acknowledge the role of modeling and avoid making claims that are much less tentative than is justified as this can lead to misleading and sometimes contrary findings in the literature. In everyday life we commonly take it for granted that finding out what another knows or thinks is a relatively trivial or straightforward process. We come to take the ‘mental register’ (the way we talk about the ‘contents’ of minds) for granted and so teachers and researchers may readily underestimate the challenges involved in their work.
Download or read book Business Model Generation written by Alexander Osterwalder and published by John Wiley & Sons. This book was released on 2013-02-01 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Model Generation is a handbook for visionaries, game changers, and challengers striving to defy outmoded business models and design tomorrow's enterprises. If your organization needs to adapt to harsh new realities, but you don't yet have a strategy that will get you out in front of your competitors, you need Business Model Generation. Co-created by 470 "Business Model Canvas" practitioners from 45 countries, the book features a beautiful, highly visual, 4-color design that takes powerful strategic ideas and tools, and makes them easy to implement in your organization. It explains the most common Business Model patterns, based on concepts from leading business thinkers, and helps you reinterpret them for your own context. You will learn how to systematically understand, design, and implement a game-changing business model--or analyze and renovate an old one. Along the way, you'll understand at a much deeper level your customers, distribution channels, partners, revenue streams, costs, and your core value proposition. Business Model Generation features practical innovation techniques used today by leading consultants and companies worldwide, including 3M, Ericsson, Capgemini, Deloitte, and others. Designed for doers, it is for those ready to abandon outmoded thinking and embrace new models of value creation: for executives, consultants, entrepreneurs, and leaders of all organizations. If you're ready to change the rules, you belong to "the business model generation!"
Download or read book Ambitious Science Teaching written by Mark Windschitl and published by Harvard Education Press. This book was released on 2020-08-05 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2018 Outstanding Academic Title, Choice Ambitious Science Teaching outlines a powerful framework for science teaching to ensure that instruction is rigorous and equitable for students from all backgrounds. The practices presented in the book are being used in schools and districts that seek to improve science teaching at scale, and a wide range of science subjects and grade levels are represented. The book is organized around four sets of core teaching practices: planning for engagement with big ideas; eliciting student thinking; supporting changes in students’ thinking; and drawing together evidence-based explanations. Discussion of each practice includes tools and routines that teachers can use to support students’ participation, transcripts of actual student-teacher dialogue and descriptions of teachers’ thinking as it unfolds, and examples of student work. The book also provides explicit guidance for “opportunity to learn” strategies that can help scaffold the participation of diverse students. Since the success of these practices depends so heavily on discourse among students, Ambitious Science Teaching includes chapters on productive classroom talk. Science-specific skills such as modeling and scientific argument are also covered. Drawing on the emerging research on core teaching practices and their extensive work with preservice and in-service teachers, Ambitious Science Teaching presents a coherent and aligned set of resources for educators striving to meet the considerable challenges that have been set for them.
Download or read book Surely You re Joking Mr Feynman Adventures of a Curious Character written by Richard P. Feynman and published by W. W. Norton & Company. This book was released on 2018-02-06 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most famous science books of our time, the phenomenal national bestseller that "buzzes with energy, anecdote and life. It almost makes you want to become a physicist" (Science Digest). Richard P. Feynman, winner of the Nobel Prize in physics, thrived on outrageous adventures. In this lively work that “can shatter the stereotype of the stuffy scientist” (Detroit Free Press), Feynman recounts his experiences trading ideas on atomic physics with Einstein and cracking the uncrackable safes guarding the most deeply held nuclear secrets—and much more of an eyebrow-raising nature. In his stories, Feynman’s life shines through in all its eccentric glory—a combustible mixture of high intelligence, unlimited curiosity, and raging chutzpah. Included for this edition is a new introduction by Bill Gates.
Download or read book Explanatory Model Analysis written by Przemyslaw Biecek and published by CRC Press. This book was released on 2021-02-15 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.
Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
Download or read book Spin Sucks written by Gini Dietrich and published by Pearson Education. This book was released on 2014 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Go beyond PR spin! Master better ways to communicate honestly and regain the trust of your customers and stakeholders with this book.
