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Author: Sarah Rose Cavanagh
Publisher:
ISBN: 9781943665358
Category : EDUCATION
Languages : en
Pages : 241
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Book Description
Informed by psychology and neuroscience, Cavanagh argues that in order to capture students' attention, harness their working memory, bolster their long-term retention, and enhance their motivation, educators should consider the emotional impact of their teaching style and course design.
Author: Sarah Rose Cavanagh
Publisher:
ISBN: 9781943665327
Category : Affective education
Languages : en
Pages : 0
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Book Description
Informed by psychology and neuroscience, Cavanagh argues that in order to capture students' attention, harness their working memory, bolster their long-term retention, and enhance their motivation, educators should consider the emotional impact of their teaching style and course design.
Author: Jules S. Damji
Publisher: O'Reilly Media
ISBN: 1492050016
Category : Computers
Languages : en
Pages : 400
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Book Description
Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow
Author: Sarah Rose Cavanagh
Publisher:
ISBN: 9781943665358
Category : EDUCATION
Languages : en
Pages : 241
Get Book
Book Description
Informed by psychology and neuroscience, Cavanagh argues that in order to capture students' attention, harness their working memory, bolster their long-term retention, and enhance their motivation, educators should consider the emotional impact of their teaching style and course design.
Author: Sarah Rose Cavanagh
Publisher: Hachette UK
ISBN: 1538713349
Category : Psychology
Languages : en
Pages : 304
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Book Description
At the crossroads between The Shallows and Presence, Hivemind is a provocative look at how communities can sync up around shared ideas, and how this hive mentality is contributing to today's polarized times. Hivemind: A collective consciousness in which we share consensus thoughts, emotions, and opinions; a phenomenon whereby a group of people function as if with a single mind. Our views of the world are shaped by the stories told by our self-selected communities. Whether seeking out groups that share our tastes, our faith, our heritage, or other interests, since the dawn of time we have taken comfort in defining ourselves through our social groups. But what happens when we only socialize with our chosen group, to the point that we lose the ability to connect to people who don't share our passions? What happens when our tribes merely confirm our world view, rather than expand it? We have always been a remarkably social species-our moods, ideas, and even our perceptions of reality synchronize without our conscious awareness. The advent of social media and smartphones has amplified these tendencies in ways that spell both promise and peril. Our hiveish natures benefit us in countless ways-combatting the mental and physical costs of loneliness, connecting us with collaborators and supporters, and exposing us to entertainment and information beyond what we can find in our literal backyards. But of course, there are also looming risks-echo chambers, political polarization, and conspiracy theories that have already begun to have deadly consequences. Leading a narrative journey from the site of the Charlottesville riots to the boardrooms of Facebook, considering such diverse topics as zombies, neuroscience, and honeybees, psychologist and emotion regulation specialist Sarah Rose Cavanagh leaves no stone unturned in her quest to understand how social technology is reshaping the way we socialize. It's not possible to turn back the clocks, and Cavanagh argues that there's no need to; instead, she presents a fully examined and thoughtful call to cut through our online tribalism, dial back our moral panic about screens and mental health, and shore up our sense of community. With compelling storytelling and shocking research, Hivemind is a must-read for anyone hoping to make sense of the dissonance around us.
Author: Ramsey Musallam
Publisher:
ISBN: 9781946444134
Category : Education
Languages : en
Pages : 166
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Book Description
Inspired by his popular TED Talk "3 Rules to Spark Learning," this book combines brain science research, proven teaching methods, and Ramsey's personal story to empower you to improve your students' learning experiences by inspiring inquiry and harnessing its benefits. If you want to engage students, this is the book for you.
Author: CRAIG. ROBINSON COVEY (LANDON. SCHWAB, PHIL.)
Publisher:
ISBN: 9781839210143
Category :
Languages : en
Pages :
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Book Description
Author: Butch Quinto
Publisher: Apress
ISBN: 1484256697
Category : Computers
Languages : en
Pages : 367
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Book Description
Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. What You Will Learn Be introduced to machine learning, Spark, and Spark MLlib 2.4.xAchieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM librariesDetect anomalies with the Isolation Forest algorithm for SparkUse the Spark NLP and Stanford CoreNLP libraries that support multiple languagesOptimize your ML workload with the Alluxio in-memory data accelerator for SparkUse GraphX and GraphFrames for Graph AnalysisPerform image recognition using convolutional neural networksUtilize the Keras framework and distributed deep learning libraries with Spark Who This Book Is For Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.
Author: Holden Karau
Publisher: "O'Reilly Media, Inc."
ISBN: 144935906X
Category : Computers
Languages : en
Pages : 276
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Book Description
This book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. You'll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.--
Author: Aurobindo Sarkar
Publisher: Packt Publishing Ltd
ISBN: 1785887351
Category : Computers
Languages : en
Pages : 452
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Book Description
Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB Perform data quality checks, data visualization, and basic statistical analysis tasks Perform data munging tasks on publically available datasets Learn how to use Spark SQL and Apache Kafka to build streaming applications Learn key performance-tuning tips and tricks in Spark SQL applications Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale.
Author: Alex Tellez
Publisher: Packt Publishing Ltd
ISBN: 1785282417
Category : Computers
Languages : en
Pages : 334
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Book Description
Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book Process and analyze big data in a distributed and scalable way Write sophisticated Spark pipelines that incorporate elaborate extraction Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn Use Spark streams to cluster tweets online Run the PageRank algorithm to compute user influence Perform complex manipulation of DataFrames using Spark Define Spark pipelines to compose individual data transformations Utilize generated models for off-line/on-line prediction Transfer the learning from an ensemble to a simpler Neural Network Understand basic graph properties and important graph operations Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.
