Deep Work

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Publisher : Grand Central Publishing
ISBN 13 : 1455586668
Total Pages : 228 pages
Book Rating : 4.4/5 (555 download)

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Book Synopsis Deep Work by : Cal Newport

Download or read book Deep Work written by Cal Newport and published by Grand Central Publishing. This book was released on 2016-01-05 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: AN AMAZON BEST BOOK OF 2O16 PICK IN BUSINESS & LEADERSHIP WALL STREET JOURNAL BUSINESS BESTSELLER A BUSINESS BOOK OF THE WEEK AT 800-CEO-READ Master one of our economy’s most rare skills and achieve groundbreaking results with this “exciting” book (Daniel H. Pink) from an “exceptional” author (New York Times Book Review). Deep work is the ability to focus without distraction on a cognitively demanding task. It's a skill that allows you to quickly master complicated information and produce better results in less time. Deep Work will make you better at what you do and provide the sense of true fulfillment that comes from craftsmanship. In short, deep work is like a super power in our increasingly competitive twenty-first century economy. And yet, most people have lost the ability to go deep-spending their days instead in a frantic blur of e-mail and social media, not even realizing there's a better way. In Deep Work, author and professor Cal Newport flips the narrative on impact in a connected age. Instead of arguing distraction is bad, he instead celebrates the power of its opposite. Dividing this book into two parts, he first makes the case that in almost any profession, cultivating a deep work ethic will produce massive benefits. He then presents a rigorous training regimen, presented as a series of four "rules," for transforming your mind and habits to support this skill. 1. Work Deeply 2. Embrace Boredom 3. Quit Social Media 4. Drain the Shallows A mix of cultural criticism and actionable advice, Deep Work takes the reader on a journey through memorable stories-from Carl Jung building a stone tower in the woods to focus his mind, to a social media pioneer buying a round-trip business class ticket to Tokyo to write a book free from distraction in the air-and no-nonsense advice, such as the claim that most serious professionals should quit social media and that you should practice being bored. Deep Work is an indispensable guide to anyone seeking focused success in a distracted world.

Deep Learning with PyTorch

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Publisher : Simon and Schuster
ISBN 13 : 1638354073
Total Pages : 518 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning with PyTorch by : Luca Pietro Giovanni Antiga

Download or read book Deep Learning with PyTorch written by Luca Pietro Giovanni Antiga and published by Simon and Schuster. This book was released on 2020-07-01 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: “We finally have the definitive treatise on PyTorch! It covers the basics and abstractions in great detail. I hope this book becomes your extended reference document.” —Soumith Chintala, co-creator of PyTorch Key Features Written by PyTorch’s creator and key contributors Develop deep learning models in a familiar Pythonic way Use PyTorch to build an image classifier for cancer detection Diagnose problems with your neural network and improve training with data augmentation Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands. Instantly familiar to anyone who knows Python data tools like NumPy and Scikit-learn, PyTorch simplifies deep learning without sacrificing advanced features. It’s great for building quick models, and it scales smoothly from laptop to enterprise. Deep Learning with PyTorch teaches you to create deep learning and neural network systems with PyTorch. This practical book gets you to work right away building a tumor image classifier from scratch. After covering the basics, you’ll learn best practices for the entire deep learning pipeline, tackling advanced projects as your PyTorch skills become more sophisticated. All code samples are easy to explore in downloadable Jupyter notebooks. What You Will Learn Understanding deep learning data structures such as tensors and neural networks Best practices for the PyTorch Tensor API, loading data in Python, and visualizing results Implementing modules and loss functions Utilizing pretrained models from PyTorch Hub Methods for training networks with limited inputs Sifting through unreliable results to diagnose and fix problems in your neural network Improve your results with augmented data, better model architecture, and fine tuning This Book Is Written For For Python programmers with an interest in machine learning. No experience with PyTorch or other deep learning frameworks is required. About The Authors Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch. Thomas Viehmann is a Machine Learning and PyTorch speciality trainer and consultant based in Munich, Germany and a PyTorch core developer. Table of Contents PART 1 - CORE PYTORCH 1 Introducing deep learning and the PyTorch Library 2 Pretrained networks 3 It starts with a tensor 4 Real-world data representation using tensors 5 The mechanics of learning 6 Using a neural network to fit the data 7 Telling birds from airplanes: Learning from images 8 Using convolutions to generalize PART 2 - LEARNING FROM IMAGES IN THE REAL WORLD: EARLY DETECTION OF LUNG CANCER 9 Using PyTorch to fight cancer 10 Combining data sources into a unified dataset 11 Training a classification model to detect suspected tumors 12 Improving training with metrics and augmentation 13 Using segmentation to find suspected nodules 14 End-to-end nodule analysis, and where to go next PART 3 - DEPLOYMENT 15 Deploying to production

Deep Learning and the Game of Go

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Publisher : Simon and Schuster
ISBN 13 : 1638354014
Total Pages : 611 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning and the Game of Go by : Kevin Ferguson

Download or read book Deep Learning and the Game of Go written by Kevin Ferguson and published by Simon and Schuster. This book was released on 2019-01-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning

Intelligent Autonomous Drones with Cognitive Deep Learning

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Publisher : Apress
ISBN 13 : 9781484268025
Total Pages : 0 pages
Book Rating : 4.2/5 (68 download)

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Book Synopsis Intelligent Autonomous Drones with Cognitive Deep Learning by : David Allen Blubaugh

Download or read book Intelligent Autonomous Drones with Cognitive Deep Learning written by David Allen Blubaugh and published by Apress. This book was released on 2022-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone. You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability. Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones. What You’ll Learn Examine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous drones Look at software and hardware requirements Understand unified modeling language (UML) and real-time UML for design Study deep learning neural networks for pattern recognition Review geo-spatial Information for the development of detailed mission planning within these hostile environments Who This Book Is For Primarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.

Build a Home-save a Third

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Publisher :
ISBN 13 :
Total Pages : 150 pages
Book Rating : 4.:/5 (31 download)

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Book Synopsis Build a Home-save a Third by : Harold Cary

Download or read book Build a Home-save a Third written by Harold Cary and published by . This book was released on 1924 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Build Deeper

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Publisher : Independently Published
ISBN 13 : 9781793223012
Total Pages : 271 pages
Book Rating : 4.2/5 (23 download)

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Book Synopsis Build Deeper by : Thimira Amaratunga

Download or read book Build Deeper written by Thimira Amaratunga and published by Independently Published. This book was released on 2019-01-09 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: New 2019 Edition! Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application. It covers: What Deep Learning is, and where it fits with Artificial Intelligence and Machine Learning. How Deep Learning came to be, its predecessors, and the path it took to evolve into what it is today. The important milestones it has passed through the years, and the impact they had on the field. What tools are available for us to learn and build deep learning applications, and how to set them up: Python, TensorFlow, Theano, Keras, and more, on any OS of your choosing: Windows, Linux, or Mac OS. Building our first simple deep learning model. The internal workings of a deep learning model. Using more advanced topics such as Data Augmentation, Transfer Learning, Bottleneck Features, and Fine Tuning to build a practical deep learning application. Getting started with Computer Vision. All you need now is a little enthusiasm ... who knows where it will take you! Go a little deeper to discover ...

Building

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Publisher :
ISBN 13 :
Total Pages : 1102 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Building by :

Download or read book Building written by and published by . This book was released on 1920 with total page 1102 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Building Machine Learning and Deep Learning Models on Google Cloud Platform

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Publisher : Apress
ISBN 13 : 1484244702
Total Pages : 703 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Building Machine Learning and Deep Learning Models on Google Cloud Platform by : Ekaba Bisong

Download or read book Building Machine Learning and Deep Learning Models on Google Cloud Platform written by Ekaba Bisong and published by Apress. This book was released on 2019-09-27 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers

Deep Learning for Coders with fastai and PyTorch

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Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

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

Codeless Deep Learning with KNIME

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Publisher : Packt Publishing Ltd
ISBN 13 : 180056242X
Total Pages : 385 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Codeless Deep Learning with KNIME by : Kathrin Melcher

Download or read book Codeless Deep Learning with KNIME written by Kathrin Melcher and published by Packt Publishing Ltd. This book was released on 2020-11-27 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key FeaturesBecome well-versed with KNIME Analytics Platform to perform codeless deep learningDesign and build deep learning workflows quickly and more easily using the KNIME GUIDiscover different deployment options without using a single line of code with KNIME Analytics PlatformBook Description KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems. Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices. By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network. What you will learnUse various common nodes to transform your data into the right structure suitable for training a neural networkUnderstand neural network techniques such as loss functions, backpropagation, and hyperparametersPrepare and encode data appropriately to feed it into the networkBuild and train a classic feedforward networkDevelop and optimize an autoencoder network for outlier detectionImplement deep learning networks such as CNNs, RNNs, and LSTM with the help of practical examplesDeploy a trained deep learning network on real-world dataWho this book is for This book is for data analysts, data scientists, and deep learning developers who are not well-versed in Python but want to learn how to use KNIME GUI to build, train, test, and deploy neural networks with different architectures. The practical implementations shown in the book do not require coding or any knowledge of dedicated scripts, so you can easily implement your knowledge into practical applications. No prior experience of using KNIME is required to get started with this book.

My Portfolio

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Publisher :
ISBN 13 :
Total Pages : 308 pages
Book Rating : 4.A/5 ( download)

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Book Synopsis My Portfolio by : Austin Phelps

Download or read book My Portfolio written by Austin Phelps and published by . This book was released on 1882 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Art of Community

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Publisher : Berrett-Koehler Publishers
ISBN 13 : 1626568421
Total Pages : 217 pages
Book Rating : 4.6/5 (265 download)

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Book Synopsis The Art of Community by : Charles Vogl

Download or read book The Art of Community written by Charles Vogl and published by Berrett-Koehler Publishers. This book was released on 2016-09-12 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create a Culture of Belonging! Strong cultures help people support one another, share their passions, and achieve big goals. And such cultures of belonging aren't just happy accidents - they can be purposefully cultivated, whether they're in a company, a faith institution or among friends and enthusiasts. Drawing on 3,000 years of history and his personal experience, Charles Vogl lays out seven time-tested principles for growing enduring, effective and connected communities. He provides hands-on tools for creatively adapting these principles to any group—formal or informal, mission driven or social, physical or virtual. This book is a guide for leaders seeking to build a vibrant, living culture that will enrich lives. Winner of the Nautilus Silver Book Award in the Business and Leadership Category.

New Pencil Points

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Publisher :
ISBN 13 :
Total Pages : 1250 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis New Pencil Points by :

Download or read book New Pencil Points written by and published by . This book was released on 1926 with total page 1250 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Facilitator Era

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Publisher : Wipf and Stock Publishers
ISBN 13 : 1621891917
Total Pages : 418 pages
Book Rating : 4.6/5 (218 download)

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Book Synopsis The Facilitator Era by : Tom Steffen

Download or read book The Facilitator Era written by Tom Steffen and published by Wipf and Stock Publishers. This book was released on 2011-01-01 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some time ago, Ralph Winter brilliantly identified three eras of modern missions: Era 1: William Carey focused on the coastlands; Era 2: Hudson Taylor focused on the inlands; Era 3: Donald McGavran and Cameron Townsend focused on unreached peoples. With all the fast and furious changes swirling around us today in twenty-first century missions, have we entered a Fourth Era? If so, who are the people primarily involved? How are they selected? How are they trained? How long do they serve? Has the Third Era ministry focus--reaching the unreached--changed? If so, to what? Are there any successful case studies out there? Have McGavran and Townsend passed the baton to a new leader(s)? If so, to whom? This book seeks to answer these and related questions. Contributors: Dr. Ben Beckner Dr. Monroe Brewer Dr. Don Finley Mike Griffis Dr. Gary Hipp, MD Jerry Hogshead Kaikou Maisu Judy Manna Kenn Oke Dr. A. Sue Russell Dr. Robert Strauss Peter Swann Bryan Thomas Diane Thomas Dr. Mike Wilson Dr. Sherwood G. Lingenfelter

A More Perfect Union

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Publisher : Broadleaf Books
ISBN 13 : 1506464548
Total Pages : 268 pages
Book Rating : 4.5/5 (64 download)

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Book Synopsis A More Perfect Union by : Adam Russell Taylor

Download or read book A More Perfect Union written by Adam Russell Taylor and published by Broadleaf Books . This book was released on 2021-09-14 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: America is at a pivotal crossroads. The soul of our nation is at stake and in peril. A new public narrative is needed to unite Americans around common values and to counter the increasing discord and acrimony in our politics and culture. The process of healing and creating a more perfect union in our nation must start now. The moral vision of Martin Luther King Jr.'s Beloved Community, which animated and galvanized the civil rights movement of the 1950s and 1960s, provides a hopeful way forward. In A More Perfect Union, Adam Russell Taylor, president of Sojourners, reimagines a contemporary version of the Beloved Community that will inspire and unite Americans across generations, geographic and class divides, racial and gender differences, faith traditions, and ideological leanings. In the Beloved Community, neither privilege nor punishment is tied to race, gender, religion, sexual orientation, or economic status, and everyone is able to realize their full potential and thrive. Building the Beloved Community requires living out a series of commitments, such as true equality, radical welcome, transformational interdependence, E Pluribus Unum ("out of many, one"), environmental stewardship, nonviolence, and economic equity. By building the Beloved Community we unify the country around a shared moral vision that transcends ideology and partisanship, tapping into our most sacred civic and religious values, enabling our nation to live up to its best ideals and realize a more perfect union.

Building Age

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Publisher :
ISBN 13 :
Total Pages : 1064 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Building Age by :

Download or read book Building Age written by and published by . This book was released on 1910 with total page 1064 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Land of Sunshine

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Publisher :
ISBN 13 :
Total Pages : 96 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Land of Sunshine by :

Download or read book Land of Sunshine written by and published by . This book was released on 1913 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes reports, etc., of the Southwest Society of the Archaeological Institutes of America.