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Author: Mike Procopio
Publisher: Packt Publishing Ltd
ISBN: 1782160493
Category : Computers
Languages : en
Pages : 147
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Book Description
This book is a Starter which teaches you how to use Google Drive practically. This book is perfect for people of all skill levels who want to enjoy the benefits of using Google Drive to safely store their files online and in the cloud. It's also great for anyone looking to learn more about cloud computing in general. Readers are expected to have an Internet connection and basic knowledge of using the internet.
Author: Mike Procopio
Publisher: Packt Publishing Ltd
ISBN: 1782160493
Category : Computers
Languages : en
Pages : 147
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Book Description
This book is a Starter which teaches you how to use Google Drive practically. This book is perfect for people of all skill levels who want to enjoy the benefits of using Google Drive to safely store their files online and in the cloud. It's also great for anyone looking to learn more about cloud computing in general. Readers are expected to have an Internet connection and basic knowledge of using the internet.
Author: Ian Lamont
Publisher: i30 Media Corporation
ISBN: 1939924626
Category : Computers
Languages : en
Pages : 81
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Book Description
Updated in 2018! The top-selling guide to Google’s free online office suite is now available in a revised and expanded second edition. Thirty minutes is all you'll need to get up to speed with Google Drive, Google Docs, Google Sheets, and Google Slides, the free online productivity suite and alternative to Microsoft Office. Millions of people use the software every day. You can use Drive, Docs, Sheets, and Slides to perform the following tasks: • Write letters and reports • Crunch numbers and create online data entry forms • Give presentations • Collaborate online with classmates and colleagues • Convert Microsoft Office documents to Google formats, and vice versa • Print documents, drawings, and spreadsheets • Export PDFs • Make pie charts, bar charts, and simple tables • Publish documents and spreadsheets online using the new Google Sites After covering registration, file creation and other basics, Google Drive and Docs In 30 Minutes (2nd Edition) zeroes in on the most important time-saving tips and productivity tools. Highlights include: • Converting files between Microsoft Office and Google formats. • Best practices for organizing files in Google Drive. • What to expect with collaboration and sharing. • The pros and cons of Google’s mobile apps for Drive, Docs, Sheets, and Slides. • Accessing older versions of files. • How to publish your documents to the Web for colleagues or members of the public to view. • Functions, sorting and filtering in Google Sheets (with examples). • Using Google Forms to gather data. • Google Slides: Is it a suitable alternative to Microsoft PowerPoint? • Working with offline files. • Downloading third-party apps. The tone of Google Drive and Docs In 30 Minutes is friendly and easy to understand, with lots of step-by-step instructions, screenshots, and examples. The guide can be used by anyone with a PC, Mac, or Chromebook. It also includes instructions for using Drive, Docs, Sheets, and Slides on Android and iOS phones and tablets. Google Drive and Docs In 30 Minutes, 2nd Edition is authored by Ian Lamont, an award-winning technology and business journalist. He has written several books in the "In 30 Minutes" series, including Dropbox In 30 Minutes, Twitter In 30 Minutes, and Excel Basics In 30 Minutes. Here's what readers are saying about Google Drive & Docs In 30 Minutes: “I am so glad this was made! I've been using Google Docs for a while now and have been encouraging my teacher colleagues to do so as well to facilitate collaboration. It has become my go-to text book to help new users understand quickly. If you're new to Google Drive or Google Documents, this will help you. If you're experienced, and want something to help those who come to you with questions, this is a nice tool to help them remember what you show them. I highly recommend it.” “I just got a new position that requires record keeping. Having used Google Docs in the past, I decided to update my knowledge. I googled "Docs for dummies" and this was one of the results. I liked the concept that the title implies - a concise guide that will distill what I need and allow me to complete a task quickly” “A clear and concise explanation of how to navigate your way through google docs.” “Excellent introduction to Google drive. Well researched, easy to read, nicely organized.”
Author: Alex Nordeen
Publisher: Guru99
ISBN:
Category : Computers
Languages : en
Pages : 365
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Book Description
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
Author: Gian Marco Iodice
Publisher: Packt Publishing Ltd
ISBN: 1837633967
Category : Computers
Languages : en
Pages : 665
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Book Description
Over 70 recipes to help you develop smart applications on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano using the power of machine learning Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Over 20+ new recipes, including recognizing music genres and detecting objects in a scene Create practical examples using TensorFlow Lite for Microcontrollers, Edge Impulse, and more Explore cutting-edge technologies, such as on-device training for updating models without data leaving the device Book DescriptionDiscover the incredible world of tiny Machine Learning (tinyML) and create smart projects using real-world data sensors with the Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano. TinyML Cookbook, Second Edition, will show you how to build unique end-to-end ML applications using temperature, humidity, vision, audio, and accelerometer sensors in different scenarios. These projects will equip you with the knowledge and skills to bring intelligence to microcontrollers. You'll train custom models from weather prediction to real-time speech recognition using TensorFlow and Edge Impulse.Expert tips will help you squeeze ML models into tight memory budgets and accelerate performance using CMSIS-DSP. This improved edition includes new recipes featuring an LSTM neural network to recognize music genres and the Faster-Objects-More-Objects (FOMO) algorithm for detecting objects in a scene. Furthermore, you’ll work on scikit-learn model deployment on microcontrollers, implement on-device training, and deploy a model using microTVM, including on a microNPU. This beginner-friendly and comprehensive book will help you stay up to date with the latest developments in the tinyML community and give you the knowledge to build unique projects with microcontrollers!What you will learn Understand the microcontroller programming fundamentals Work with real-world sensors, such as the microphone, camera, and accelerometer Implement an app that responds to human voice or recognizes music genres Leverage transfer learning with FOMO and Keras Learn best practices on how to use the CMSIS-DSP library Create a gesture-recognition app to build a remote control Design a CIFAR-10 model for memory-constrained microcontrollers Train a neural network on microcontrollers Who this book is for This book is ideal for machine learning engineers or data scientists looking to build embedded/edge ML applications and IoT developers who want to add machine learning capabilities to their devices. If you’re an engineer, student, or hobbyist interested in exploring tinyML, then this book is your perfect companion. Basic familiarity with C/C++ and Python programming is a prerequisite; however, no prior knowledge of microcontrollers is necessary to get started with this book.
Author: Mike Riley
Publisher: Pragmatic Bookshelf
ISBN: 1680509519
Category : Computers
Languages : en
Pages : 255
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Book Description
Discover easy ways to control your home with the powerful new Raspberry Pi hardware. Program short Python scripts that will detect changes in your home and react with the instructions you code. Use new add-on accessories to monitor a variety of measurements, from light intensity and temperature to motion detection and water leakage. Expand the base projects with your own custom additions to perfectly match your own home setup. Most projects in the book can be completed in under an hour, giving you more time to enjoy and tweak your autonomous creations. No breadboard or electronics knowledge required! Get to know the latest Raspberry Pi hardware, and create awesome automation solutions for home or work that don't require an electronics degree, cumbersome add-ons, or expensive third-party subscription services. Create easy to run Python scripts on your own that make your Pi do things that would have required a team of automation experts to build only a few years ago. Connect to and control popular home automation lighting systems from a Raspberry Pi. Trigger autonomous actions based on movement, temperature, and timer events. Power on your own computer and appliances using your voice. Remotely control infrared-enabled consumer electronics, create chatbots to retrieve personalized items of interest, and implement a temperature-monitoring room fan. These are just some of the projects that the book will show you how to make. Most projects can be completed and operational in under an hour, and do not require any messy schematics or a spaghetti bowl of wires and breadboard-attached circuits to operate. Control your home or office exactly the way you want instead of relying on an expensive mysterious box of third-party technology to do it for you. What You Need: Raspberry Pi (Pi 4 Model B or higher recommended) running Raspberry Pi OS
Author: Christoph Scheuch
Publisher: CRC Press
ISBN: 1000858715
Category : Business & Economics
Languages : en
Pages : 268
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Book Description
This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with R, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using the tidyverse family of R packages. We then provide the code to prepare common open source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques. Highlights 1. Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader’s research or as a reference for courses on empirical finance. 2. Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copy-pasting the code we provide. 3. A full-fledged introduction to machine learning with tidymodels based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods. 4. Chapter 2 on accessing and managing financial data shows how to retrieve and prepare the most important datasets in the field of financial economics: CRSP and Compustat. The chapter also contains detailed explanations of the most relevant data characteristics. 5. Each chapter provides exercises that are based on established lectures and exercise classes and which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.
Author: V Kishore Ayyadevara
Publisher: Packt Publishing Ltd
ISBN: 1839216530
Category : Computers
Languages : en
Pages : 805
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Book Description
Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questions Key FeaturesImplement solutions to 50 real-world computer vision applications using PyTorchUnderstand the theory and working mechanisms of neural network architectures and their implementationDiscover best practices using a custom library created especially for this bookBook Description Deep learning is the driving force behind many recent advances in various computer vision (CV) applications. This book takes a hands-on approach to help you to solve over 50 CV problems using PyTorch1.x on real-world datasets. You’ll start by building a neural network (NN) from scratch using NumPy and PyTorch and discover best practices for tweaking its hyperparameters. You’ll then perform image classification using convolutional neural networks and transfer learning and understand how they work. As you progress, you’ll implement multiple use cases of 2D and 3D multi-object detection, segmentation, human-pose-estimation by learning about the R-CNN family, SSD, YOLO, U-Net architectures, and the Detectron2 platform. The book will also guide you in performing facial expression swapping, generating new faces, and manipulating facial expressions as you explore autoencoders and modern generative adversarial networks. You’ll learn how to combine CV with NLP techniques, such as LSTM and transformer, and RL techniques, such as Deep Q-learning, to implement OCR, image captioning, object detection, and a self-driving car agent. Finally, you'll move your NN model to production on the AWS Cloud. By the end of this book, you’ll be able to leverage modern NN architectures to solve over 50 real-world CV problems confidently. What you will learnTrain a NN from scratch with NumPy and PyTorchImplement 2D and 3D multi-object detection and segmentationGenerate digits and DeepFakes with autoencoders and advanced GANsManipulate images using CycleGAN, Pix2PixGAN, StyleGAN2, and SRGANCombine CV with NLP to perform OCR, image captioning, and object detectionCombine CV with reinforcement learning to build agents that play pong and self-drive a carDeploy a deep learning model on the AWS server using FastAPI and DockerImplement over 35 NN architectures and common OpenCV utilitiesWho this book is for This book is for beginners to PyTorch and intermediate-level machine learning practitioners who are looking to get well-versed with computer vision techniques using deep learning and PyTorch. If you are just getting started with neural networks, you’ll find the use cases accompanied by notebooks in GitHub present in this book useful. Basic knowledge of the Python programming language and machine learning is all you need to get started with this book.
Author: María Carina Roldán
Publisher: Packt Publishing Ltd
ISBN: 1789342791
Category : Computers
Languages : en
Pages : 174
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Book Description
Get productive quickly with Pentaho Data Integration Key Features Take away the pain of starting with a complex and powerful system Simplify your data transformation and integration work Explore, transform, and validate your data with Pentaho Data Integration Book Description Pentaho Data Integration(PDI) is an intuitive and graphical environment packed with drag and drop design and powerful Extract-Transform-Load (ETL) capabilities. Given its power and flexibility, initial attempts to use the Pentaho Data Integration tool can be difficult or confusing. This book is the ideal solution. This book reduces your learning curve with PDI. It provides the guidance needed to make you productive, covering the main features of Pentaho Data Integration. It demonstrates the interactive features of the graphical designer, and takes you through the main ETL capabilities that the tool offers. By the end of the book, you will be able to use PDI for extracting, transforming, and loading the types of data you encounter on a daily basis. What you will learn Design, preview and run transformations in Spoon Run transformations using the Pan utility Understand how to obtain data from different types of files Connect to a database and explore it using the database explorer Understand how to transform data in a variety of ways Understand how to insert data into database tables Design and run jobs for sequencing tasks and sending emails Combine the execution of jobs and transformations Who this book is for This book is for software developers, business intelligence analysts, and others involved or interested in developing ETL solutions, or more generally, doing any kind of data manipulation.
Author: Guy Hart-Davis
Publisher: John Wiley & Sons
ISBN: 1119763312
Category : Computers
Languages : en
Pages : 387
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Book Description
Master the ins and outs of Google's free-to-use office and productivity software Teach Yourself VISUALLY Google Workspace delivers the ultimate guide to getting the most out of Google's Workspace cloud software. Accomplished author Guy Hart-Davis offers readers the ability to tackle a huge number of everyday productivity problems with Google's intuitive collection of online tools. With over 700 full-color screenshots included to help you learn, you'll discover how to: Manage your online Google Calendar Master the files and folders in your Google Drive storage Customize your folders and navigate your Gmail account Create perfect spreadsheets, presentations, and documents in Google Sheets, Slides, and Docs Perfect for anyone who hopes to make sense of Google's highly practical and free online suite of tools, Teach Yourself VISUALLY Google Workspace also belongs on the bookshelves of those who already find themselves using Workspace and just want to get more out of it.
Author: Noah Robinson
Publisher: Createspace Independent Publishing Platform
ISBN: 9781535183383
Category : Cloud computing
Languages : en
Pages : 42
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Book Description
Google Drive, which was formerly called Google Docs, is an efficient file storage and management service extended by Google.
