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Where advanced technology meets security, the DVA3221 32-Channel Deep Learning NVR by Synology stands out. This state-of-the-art Network Video Recorder (NVR) integrates a powerful video management system with AI-driven analytics, transforming video surveillance into a smarter, more efficient tool. The DVA3221 is capable of handling up to 32 camera feeds simultaneously, providing real-time statistics and alerts for immediate action. It supports six real-time tasks and offers scalability up to 14 drives with two DX517, making it a robust solution for comprehensive surveillance needs. This NVR is equipped with advanced deep learning-based analytics that transform video footage into actionable insights, enhancing security operations without the need for additional personnel. It offers people and vehicle detection features, enabling the system to identify individuals or vehicles in restricted areas, thereby increasing situational awareness. The DVA3221 is powered by Synology DSM, ensuring all footage is stored on the device with flexible backup or archiving options to other devices and locations. This on-prem recording and analytics system prioritizes security and privacy, ensuring no footage is uploaded to the cloud for storage or analysis. This one-time hardware and license purchase comes with no recurring fees or additional charges for software updates. It provides real-time results, notifying security operators immediately when incidents occur, rather than relying on post-event analysis. The DVA3221 is compatible with over 7,600 IP cameras and supports ONVIF, eliminating the need to replace or be locked into a specific brand of cameras. It's an all-in-one NVR solution that combines video recording, analysis, and advanced video management. With the DVA3221, you can set up security policies to trigger corresponding actions automatically when a condition is met, reducing the time and effort needed for manual interventions. It's designed to be user-friendly for both administrators and operators, simplifying the tasks of adding and managing cameras, navigating between live feeds and recordings, and configuring permissions and backup tasks. Access your surveillance system on any system through a browser, our PC/Mac/Linux client, or through mobile apps, with or without internet access. The DVA3221 is API ready, with comprehensive documentation available for third-party developers looking to integrate their products or applications with Surveillance Station. With the DVA3221, you get one-stop support for both the hardware and software solution, simplifying setup and maintenance efforts. Experience the future of video surveillance with the DVA3221 32-Channel Deep Learning NVR.

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Create learning experiences that transform not only learning, but life itself. Learn about, improve, and expand your world of learning. This hands-on companion to the runaway best-seller, Deep Learning: Engage the World Change the World, provides an essential roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Loaded with tips, tools, protocols, and real-world examples, the easy-to-use guide has everything educators need to construct and drive meaningful deep learning experiences that give purpose, unleash student potential, and prepare students to become problem-solving change agents in a global society. 

Have you ever wondered what makes storytelling and digital media a powerful combination? This edited volume examines the opportunities to think, do, and/or create jointly afforded by digital storytelling. The editors of this volume contend that digital storytelling and digital media can create spaces of empowerment and transformation by facilitating multiple kinds of border crossings and convergences involving groups of peoples, places, knowledge, methodologies, and teaching pedagogies.The book is unique in its inclusion of anthropologists and education practitioners and its emphasis on multiple subfields in anthropology.The contributors discuss digital storytelling in the context of educational programs, teaching anthropology, and ethnographic research involving a variety of populations and subjects that will appeal to researchers and practitioners engaged with qualitative methods and pedagogies that rely on media technology.

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Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models, and world models.Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative.Discover how variational autoencoders can change facial expressions in photosBuild practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generationCreate recurrent generative models for text generation and learn how to improve the models using attentionUnderstand how generative models can help agents to accomplish tasks within a reinforcement learning settingExplore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

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Play is serious business. Whether it's reenacting a favorite book (comprehension and close reading), negotiating the rules for a game (speaking and listening), or collaborating over building blocks (college and career readiness and STEM), Kristi Mraz, Alison Porcelli, and Cheryl Tyler see every day how play helps students reach standards and goals in ways that in-their-seat instruction alone can't do. And not just during playtimes. "We believe there is play in work and work in play," they write. "It helps to have practical ways to carry that mindset into all aspects of the curriculum." In Purposeful Play , they share ways to: optimize and balance different types of play to deepen regular classroom learning teach into play to foster social-emotional skills and a growth mindset bring the impact of play into all your lessons across the day. "We believe that play is one type of environment where children can be rigorous in their learning," Kristi, Alison, and Cheryl write. So they provide a host of lessons, suggestions for classroom setups, helpful tools and charts, curriculum connections, teaching points, and teaching language to help you foster mature play that makes every moment in your classroom instructional. Play doesn't only happen when work is over. Children show us time and time again that play is the way they work. In Purposeful Play, you'll find research-driven methods for making play an engine for rigorous learning in your classroom.

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Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations.Explore computational graphs and the supervised learning paradigmMaster the basics of the PyTorch optimized tensor manipulation libraryGet an overview of traditional NLP concepts and methodsLearn the basic ideas involved in building neural networksUse embeddings to represent words, sentences, documents, and other featuresExplore sequence prediction and generate sequence-to-sequence modelsLearn design patterns for building production NLP systems

Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results. Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, NLP expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Your expert resource to activate, manage, and maintain lasting student success! Student disengagement is a huge challenge for teachers everywhere. Leading education expert Jennifer Fredricks empowers teachers to reenga