Download or read book Blank Screenwriting Notebook Write Your Own Movies 200 Pages of Pre Formatted Script Templates 8 5 X 11 Journal for Ideas Notes in Sidebars for Writers of TV Shows and Films written by P. E. Robinson and published by . This book was released on 2019-10-29 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: A 200-Page pre-formatted notebook to spill out your film and TV scripts by hand. Our Vomit Draft Blank Screenwriting Notebooks are simple and provide visual guidelines on every page to help shape your words into industry-style screenplays. Unlock your wildest spec film and TV scripts without pre-editing or time-wasting like many do in front of a keyboard. Click on AUTHOR name for 8 journal colors! * Matte cover; write Title on Spine. * Guides for 'Titles, Slug Lines, Action, Dialogue, Characters, Page #s & Dates.' * Title page. * 3-Act brainstorming pages. * 'Notes & Objectives' sidebars. * 8 Scene bubbles to easily spot location changes later. * 40 Horizontal lines are numbered. * 200 Pages in all; 96 script pages, if using single-sided. * Full-Bleed design. * NO digital distractions. * NO staring at blank white computer screens. * NO more lost concepts. All ideas, one place. * NO more batteries, cables or clutter. * TRAVEL and write wherever you get a spark! VOMIT DRAFT: END PROCRASTINATION or GIFT ONE TO A WRITER.

Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Download or read book R Markdown written by Yihui Xie and published by CRC Press. This book was released on 2018-07-27 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. In this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents. Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown. J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix. Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse.

Download or read book Applied Deep Learning with Python written by Alex Galea and published by Packt Publishing Ltd. This book was released on 2018-08-31 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to deep learning that’s filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who don’t have a data science background Covers the key foundational concepts you’ll need to know when building deep learning systems Full of step-by-step exercises and activities to help build the skills that you need for the real-world Book Description Taking an approach that uses the latest developments in the Python ecosystem, you’ll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We’ll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It’s okay if these terms seem overwhelming; we’ll show you how to put them to work. We’ll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It’s after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data. By guiding you through a trained neural network, we’ll explore common deep learning network architectures (convolutional, recurrent, generative adversarial) and branch out into deep reinforcement learning before we dive into model optimization and evaluation. We’ll do all of this whilst working on a production-ready web application that combines Tensorflow and Keras to produce a meaningful user-friendly result, leaving you with all the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively. What you will learn Discover how you can assemble and clean your very own datasets Develop a tailored machine learning classification strategy Build, train and enhance your own models to solve unique problems Work with production-ready frameworks like Tensorflow and Keras Explain how neural networks operate in clear and simple terms Understand how to deploy your predictions to the web Who this book is for If you're a Python programmer stepping into the world of data science, this is the ideal way to get started.

Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Download or read book The Godfather Notebook written by Francis Ford Coppola and published by Simon and Schuster. This book was released on 2016-12-20 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE PUBLISHING SENSATION OF THE YEAR FOR EVERY FILM FAN The never-before-published edition of Francis Ford Coppola’s notes and annotations on The Godfather novel by Mario Puzo reveals the story behind one of the world’s most iconic films. The most important unpublished work on one of the greatest films of all time, The Godfather, written before filming, by the man who wrote and directed it—Francis Ford Coppola, then only thirty-two years old—reveals the intense creative process that went into making this seminal film. With his meticulous notes and impressions of Mario Puzo’s novel, the notebook was referred to by Coppola daily on set while he directed the movie. The Godfather Notebook pulls back the curtain on the legendary filmmaker and the film that launched his illustrious career. Complete with an introduction by Francis Ford Coppola and exclusive photographs from on and off the set, this is a unique, beautiful, and faithful reproduction of Coppola’s original notebook. This publication will change the way the world views the iconic film—and the process of filmmaking at large. A must-have book of the season. Nothing like it has ever been published before

Download or read book bookdown written by Yihui Xie and published by CRC Press. This book was released on 2016-12-12 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats, including LaTeX/PDF, HTML, EPUB, and Word, thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book, but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers, reports, dissertations, course handouts, study notes, and even novels. You do not have to use R, either. Other choices of computing languages include Python, C, C++, SQL, Bash, Stan, JavaScript, and so on, although R is best supported. You can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub.

Download or read book Natural Language Processing with Transformers Revised Edition written by Lewis Tunstall and published by "O'Reilly Media, Inc.". This book was released on 2022-05-26 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments

Download or read book IPython Interactive Computing and Visualization Cookbook written by Cyrille Rossant and published by Packt Publishing Ltd. This book was released on 2014-09-25 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

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 Windows 7 and Vista Guide to Scripting Automation and Command Line Tools written by Brian Knittel and published by Pearson Education. This book was released on 2010-12-01 with total page 1196 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE ONLY HANDS-ON, UP-TO-DATE GUIDE TO VBSCRIPT, THE WINDOWS COMMAND LINE, AND WINDOWS POWERSHELL Windows 7 and Vista contain state-of-the-art tools for streamlining or automating virtually any system management task. If you’re a power user, administrator, or developer, these tools can help you eliminate repetitive work and manage your systems far more reliably and effectively. Renowned Windows expert Brian Knittel brings together the practical knowledge you need to use all these tools, including VBScript and Windows Scripting Host (WSH), traditional batch files, the advanced PowerShell command console, and more. Using plenty of examples, Knittel explains how each tool works, and how to solve real-world problems with them. You’ll master techniques ranging from accessing files to manipulating the Registry, sending automated emails to configuring new users. Knittel also provides concise, handy references to Windows 7/Vista’s command line, GUI scripting, and object-based management tools. The only single-source guide to all leading methods of Windows scripting and automation, this book will help you get far more done–in far less time! Understand Windows Scripting Host (WSH) and the modern Windows scripting environment Script objects with VBScript, JScript, ActivePerl, and ActivePython Read and write files, including XML and HTML files Manipulate programs and shortcuts Manage network, printer, and fax connections Make the most of PowerShell under Windows 7 and Vista Monitor and administer Windows systems with Windows Management Interface (WMI) Use ADSI to control Active Directory and Microsoft Exchange, and manage users more efficiently Avoid mistakes that can compromise script security Use Windows’ debugging tools to test and troubleshoot scripts Develop batch files that take full advantage of the command line Send faxes and email messages from scripts with Windows Fax and Collaboration Data Objects (CDO) Deploy your scripts throughout your organization Brian Knittel has been a software developer for more than 30 years. He has coauthored five titles in Que’s Special Edition Using series, covering Microsoft Windows Vista, XP, and 2000. He is also author of Windows XP Under the Hood, and coauthor of Upgrading and Repairing Windows (with Scott Mueller).

Download or read book Scripting the Life You Want written by Royce Christyn and published by Simon and Schuster. This book was released on 2020-04-07 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide to the process of “scripting” your future and successfully manifesting what you want in life • Explores the science behind how the scripting method works and shares the vivid journal entries from the author’s big breakthrough--when he successfully used his method to land a lead role on a TV show • Details how the understanding of incredible new (and, until now, mostly unheard of) scientific discoveries and emerging technologies is the most important key to creating and manifesting in your life • Reveals fun, easy tools for manifesting and self-help, updated for a new generation In this step-by-step guide, filled with success stories and practical exercises, Royce Christyn details a simple “scripting” process for harnessing the Law of Attraction and manifesting what you want in your life--happiness, wealth, travel, love, health, the perfect career, or simply a productive day. The process is backed by science and experience, yet it feels like magic. And all you need is a pen and paper. Inspired by New Thought and Positive Thinking classics, Christyn explains how he developed his scripting method through 4 years of trial and error, keeping what worked and dropping what didn’t until he brought his success rate from 5% to nearly 100%. Sharing pages from his own journals, he outlines how to create the life you want with daily journaling exercises, beginning with a simple list-making practice to figure out your wants and intentions and then progressing to actual scripting of your future, whether the next 12 hours or the next 10 days. He shows how, over time, your scripts will increase in accuracy until they converge with reality. He shares the vivid entries from his big breakthrough--when he successfully used his method to land a lead guest-starring role on Disney Channel’s Wizards of Waverly Place with Selena Gomez. He explores how “feeling” your future success as you write your daily scripts helps attract your desired outcomes, and he shares the key phrases to include to make your script come true. The author also explores the science behind how the scripting method works, including a down-to-earth examination of quantum mechanics. From small dreams to lifelong goals, this book gives you the tools to put your thoughts into action and finally close the gap between where you are and where you want to be in your life.

Download or read book Learning Jupyter written by Dan Toomey and published by Packt Publishing Ltd. This book was released on 2016-11-30 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter About This Book Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc Who This Book Is For This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner. What You Will Learn Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook Use interactive widgets to manipulate and visualize data in real time Start sharing your Notebook with colleagues Invite your colleagues to work with you in the same Notebook Organize your Notebook using Jupyter namespaces Access big data in Jupyter In Detail Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more. This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we'll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode. Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book. Style and approach This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. It demonstrates the integration of various programming languages with Jupyter Notebook through hands-on examples in every chapter.

Download or read book Developing Kaggle Notebooks written by Gabriel Preda and published by Packt Publishing Ltd. This book was released on 2023-12-27 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printed in Color Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact Leverage the power of Generative AI with Kaggle Models Purchase of the print or Kindle book includes a free PDF eBook Key Features Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound Improve the style and readability of your Notebooks, making them more impactful and compelling Book DescriptionDeveloping Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques. For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable. Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.What you will learn Approach a dataset or competition to perform data analysis via a notebook Learn data ingestion and address issues arising with the ingested data Structure your code using reusable components Analyze in depth both small and large datasets of various types Distinguish yourself from the crowd with the content of your analysis Enhance your notebook style with a color scheme and other visual effects Captivate your audience with data and compelling storytelling techniques Who this book is for This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any background Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings Professionals who already use Kaggle for learning and competing

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 Learning Jupyter 5 written by Dan Toomey and published by Packt Publishing Ltd. This book was released on 2018-08-30 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter Key Features Learn how to use Jupyter 5.x features such as cell tagging and attractive table styles Leverage big data tools and datasets with different Python packages Explore multiple-user Jupyter Notebook servers Book Description The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you’ve explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. What you will learn Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook Use interactive widgets to manipulate and visualize data in real time Start sharing your Notebook with colleagues Invite your colleagues to work with you on the same Notebook Organize your Notebook using Jupyter namespaces Access big data in Jupyter for dealing with large datasets using Spark Who this book is for Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively.

Download or read book Grease written by Randal Kleiser and published by HarperCollins. This book was released on 2019-12-03 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive and beautifully designed, Grease: The Director's Notebook also includes all new exclusive interviews with the key cast members and crew, including Olivia Newton-John, John Travolta, and Stockard Channing, original script pages, call sheets, conceptual images, and more. Grease is the word . . . Released more than four decades ago, the film version of Grease is one of the highest-grossing musicals of all time and a bona fide global sensation with legions of devoted fans across generations. For the first time ever, the film’s director, Randal Kleiser, looks back at the making of this legendary cultural landmark. Created in conjunction with Paramount Pictures and authorized by Jim Jacobs and Warren Casey (via his Estate), the creators of the original musical stage play, Grease: The Director’s Notebook features rare and never-before-seen imagery from the studio’s archives, as well as Kleiser's production notes, dialogue changes, and more. The book’s heart is Kleiser’s own heavily annotated shooting script, along with his storyboards and sketches—including lines from the play that were added to the film’s script. Grease: The Director’s Notebook is a fitting tribute to this revered international phenomenon and the one book the movie’s adoring fans will want. TM & © 2019 Paramount Pictures. All Rights Reserved. TM & © 2019 James H. Jacobs Trust and Trust Under The Will of Warren Casey. All Rights Reserved.