Search results for "Nextgen Learning Lab"
Items we need to order for you
R 336.00
Principles and Labs for Deep Learning
Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub. Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome. Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning.
R 3,678.00
Foundations of Deep Reinforcement Learning
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games–such as Go, Atari games, and DotA 2–to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problemExplore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER)Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO)Understand how algorithms can be parallelized synchronously and asynchronouslyRun algorithms in SLM Lab and learn the practical implementation details for getting deep RL to workExplore algorithm benchmark results with tuned hyperparametersUnderstand how deep RL environments are designed Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
R 1,628.00
Databricks Certified Generative AI Engineer Associate Study Guide
As generative AI becomes central to modern data and machine learning workflows, earning the Databricks Certified Generative AI Engineer Associate certification signals both credibility and technical fluency. This study guide prepares you for this sought-after certification with comprehensive coverage of core GenAI and LLM concepts, practical data management using Delta Lake, and retrieval-augmented generation (RAG) application workflows on the Databricks platform. Written by AI expert Rajaniesh Kaushikk, this book combines hands-on labs, real-world examples, and exam-aligned content to help you build and deploy effective GenAI applications. From prompt engineering and RAG-based solutions to model governance with Unity Catalog, MLflow tracking, and leveraging Hugging Face models in GenAI workflows, this guide supports both your certification journey and real-world AI development. Understand the fundamentals of generative AI, LLMs, and vector databasesPrepare and manage large-scale data using Delta Lake and the data lakehouseBuild and deploy generative AI models with Databricks and MLflowExplore RAG for enhanced model performanceImplement responsible AI practices and model governance with Unity Catalog
R 1,824.00
Emerging Technologies for Next Generation Learning Spaces
This book discusses the development of the next generation learning spaces with emerging technologies. These spaces result from the combined needs of classroom stakeholders, such as instructors and learners, with classroom elements, such as tools and technologies, pedagogy and content. The book presents discussions and studies on issues, possibilities and implications of these changes for next generation education. Novel ideas, and studies on these all-encompassing, blended roles of technologies in next generation learning spaces are clearly presented. Suggestions on how the benefits they offer can be maximized are also discussed. Engaging learning technologies have remained central in education for assisting instructors to teach and learners to learn, more effectively. However, recent technological growth is creating a system in which previous divides between key classroom concepts and stakeholders are getting progressively blurred. This is giving rise to next generation learning spaces where elements and stakeholders are blended into one. The book addresses the future of learning environments based on these perspectives.
R 3,170.98
Next Generation Digital Tools and Applications for Teaching and Learning Enhancement
Digital tools and applications are an intricate part of many classroom communities. In the field of education, there is a need to continually monitor the digital landscape and keep up to date on the tools and applications that are available to classroom teachers and K-12 students. Understanding the ever-changing digital landscape and its impact on teaching and learning is critical to using digital tools and applications effectively and in ways that enhance students' opportunities to learn. Next Generation Digital Tools and Applications for Teaching and Learning Enhancement is a critical scholarly publication that explores digital tools and applications for the PreK-12 classroom and how digital technology can enhance the preparation of teachers. Featuring a wide range of topics including education equity, social media, and teacher education, this book is essential for educators, academicians, curriculum designers, educational software developers, IT specialists, library specialists, researchers, and practitioners.
R 6,389.10
Deeper Learning
"I felt like I walked the walk and could implement many of the strategies after reading it once."—Andrea Golarz-Ziemba, TeacherO.P. Morton Elementary School, Hobart, IN"If our newest teachers came out of college with this knowledge, supplemented with the learning standards, their students would be more successful from day one."—Patti Larche, Director of Curriculum and InstructionPhelps-Clifton Springs CSD, NYPractical strategies to take your students′ understanding from "So what?" to "Wow!"With the amount of content that teachers have to teach, how can we ensure that students gain a deep and lasting understanding of what they have learned? Based on the most current research on cognition and the brain, this exciting book for Grades 4–12 provides teachers with a systematic, reflective approach to incorporating powerful learning and content processing techniques into everyday instruction.Nationally recognized experts Eric Jensen and LeAnn Nickelsen outline the Deeper Learning Cycle (DELC), an instructional model that incorporates brain research, standards, and individual learning differences, to help educators teach for deeper understanding and critical thinking. This invaluable resource includes:In-depth chapters explaining the seven stages of the DELC: planning with standards and curriculum, pre-assessing, building a positive learning culture, priming and activating prior knowledge, acquiring new knowledge, processing the learning, and evaluating student learningA Deeper Learning lesson plan template to apply to daily instruction50 strategies to differentiate instruction based on learning levels and to help students process content in meaningful ways Reflection questions to help teachers apply the material to their own practiceDeeper Learning is a powerful tool to promote and support student progress beyond the surface level of understanding in any subject area.
R 1,502.02
Data-Driven Learning for the Next Generation
Despite advancements in and availability of corpus software in language classrooms facilitating data-driven learning (DDL), the use of such methods with pre-tertiary learners remains rare. This book specifically explores the affordances of DDL for younger learners, testing its viability with teachers and students at the primary and secondary years of schooling. It features eminent and up-and-coming researchers from Europe, Asia, and Australasia who seek to address best practice in implementing DDL with younger learners, while providing a wealth of empirical findings and practical DDL activities ready for use in the pre-tertiary classroom.Divided into three parts, the volume's first section focuses on overcoming emerging challenges for DDL with younger learners, including where and how DDL can be integrated into pre-tertiary curricula, as well as potential barriers to this integration. It then considers new, cutting-edge innovations in corpora and corpus software for use with younger learners in the second section, before reporting on actual DDL studies performed with younger learners (and/or their teachers) at the primary and secondary levels of education.This book will appeal to post-graduate students, academics and researchers with interests in corpus linguistics, second language acquisition, primary and secondary literacy education, and language and educational technologies.
R 2,359.01
Learning Under the Lens
Learning Under the Lens: Applying Findings from the Science of Learning to the Classroom highlights the innovative approach being undertaken by researchers from the disparate fields of neuroscience, education and psychology working together to gain a better understanding of how we learn, and its potential to impact student learning outcomes.The book is structured in four parts: ‘Science of learning: a policy perspective’ sets the scene for this emerging field of research; ‘Self regulation of learning’ and ‘Technology and learning’ feature findings by eminent international and national researchers in the field and provides an insight into some of the innovative research illustrating the depth, breadth and multi-disciplinarity of the research; and ‘Research translation’ focuses on the scaled-up implementation of research findings in authentic learning settings, and showcases research findings which are having impact in learning environments.This fascinating book is intended as a reference tool to create awareness among researchers, policy makers, and education practitioners of the research being undertaken in the science of learning field and its potential to impact student learning outcomes.
R 9,312.18
