Funcraft - The unofficial Math Coloring Book: Minecraft Minis PDF Download
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Author: Theo von Taane Publisher: BoD – Books on Demand ISBN: 3743137526 Category : Education Languages : en Pages : 42
Book Description
Recommended age: 6-10 years You are a fan of Minecraft and you like coloring? Then, this is the perfect book for you! There are 30 pictures of your favorite Minecraft creatures in cute mini format, like Baby Zombie, Baby Creeper, Baby Bunny and many other to color. Practise your multiplication, substraction, division and addition skills. Solve the exercises and use the key below the picture to find the correct colors for the different squares. The pictures provide exercises in basic (1st & 2nd Grade) and advanced levels (3rd & 4th Grade). The only things you need to start the fun are this book and colored pencils. A must have for all young fans of Minecraft.
Author: Theo von Taane Publisher: BoD – Books on Demand ISBN: 3743137526 Category : Education Languages : en Pages : 42
Book Description
Recommended age: 6-10 years You are a fan of Minecraft and you like coloring? Then, this is the perfect book for you! There are 30 pictures of your favorite Minecraft creatures in cute mini format, like Baby Zombie, Baby Creeper, Baby Bunny and many other to color. Practise your multiplication, substraction, division and addition skills. Solve the exercises and use the key below the picture to find the correct colors for the different squares. The pictures provide exercises in basic (1st & 2nd Grade) and advanced levels (3rd & 4th Grade). The only things you need to start the fun are this book and colored pencils. A must have for all young fans of Minecraft.
Author: Joe Byerly Publisher: Fulton Books, Inc. ISBN: 1638600848 Category : Business & Economics Languages : en Pages : 109
Book Description
My Green Notebook: "Know Thyself" Before Changing Jobs is a guided reflection developed to draw out your lessons learned and help you thrive as a leader as you take on positions of increased responsibility, regardless of your line of work. We believe that reading, writing, and reflection are the keys to self-improvement and development. This notebook is your opportunity to spend a few minutes with yourself each day for a month and examine your experiences so that you can better understand your strengths and weaknesses and, more importantly, determine your opportunities for growth. "The book is original, innovative, invaluable--a portal into the mindset of a leader and a guide for the rest of us in enhancing our own mindfulness and self-awareness." Steven Pressfield, Bestselling author of Gates of Fire and The War of Art "When you change jobs, you are expressing your values. You'll choose much more wisely and get much further faster if you slow down at this critical juncture and get explicit with yourself about your values. This book will help you get to know yourself a little better, so you can make a better choice about your next step." Kim Scott, Bestselling author of Radical Candor "An innovative and useful tool for the difficult, and often-overlooked, task of critical self-evaluation" General Stanley McChrystal, U.S. Army (Retired)
Author: Shih-Chia Huang Publisher: Academic Press ISBN: 0323901999 Category : Science Languages : en Pages : 366
Book Description
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. - Introduces readers to the usefulness of neural networks and Deep Learning methods - Provides readers with in-depth understanding of the architecture and operation of Deep Convolutional Neural Networks - Demonstrates the visualization needed for designing neural networks - Provides readers with an in-depth understanding of regression problems, binary classification problems, multi-category classification problems, Variational Auto-Encoder, Generative Adversarial Network, and Object detection
Author: Debra J. Smith Publisher: iUniverse ISBN: 1440122547 Category : Business & Economics Languages : en Pages : 122
Book Description
Visualize a typical product-training program: large audiences, death by PowerPoint, and attendees secretly texting away on their cell phones. And the managers? Well, they have left the room. The truth is that adults (such as salespeople!) do not learn, much less retain, information presented to them using passive (thus boring!) training methods. Adequate training does not necessarily mean adequate content: many product training programs offer abundant and excellent product training material. The way that people are trained that is, the strategic approach to behavioral modification is as important as what people are trained on. Thus, a paradigm shift in training strategy may be indicated by introducing innovative learning techniques into the product training environment. After reading this book, you'll be able to take steps to Use blended learning principles in a holistic approach to increase learning retention Make use of the most innovative training techniques Harness the power of Adult Learning Theory Maximize learning using a small group setting Learn how to use real-life case studies to enhance learning And much more! If you are still under the impression that adequate content ensures adequate training, then think again. Take the strategic approach to allow employees to retain more of what they learn and increase sales. While targeted at companies with advanced technologies, anyone can benefit from reading this book. Take yourself and your employees to the next level and learn the secrets behind Innovations in Product Training.
Author: Glen O. Gabbard Publisher: American Psychiatric Pub ISBN: 9781585622160 Category : Psychology Languages : en Pages : 1000
Book Description
A staple of psychiatric practice, this edition reflects clinical expertise in an accessible volume. It covers all major treatments in psychiatry linked to specific disorders, with a pluralistic approach including all major treatment modalities. Each chapter has been completely updated and is organized along the lines of DSM-IV-TR.
Author: Ali Madani Publisher: Packt Publishing Ltd ISBN: 1800201133 Category : Computers Languages : en Pages : 345
Book Description
Master reproducible ML and DL models with Python and PyTorch to achieve high performance, explainability, and real-world success Key Features Learn how to improve performance of your models and eliminate model biases Strategically design your machine learning systems to minimize chances of failure in production Discover advanced techniques to solve real-world challenges Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDebugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques. It goes beyond the basics to arm you with the expertise essential for building reliable, high-performance models for industrial applications. Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies. By bridging the gap between theory and practice, you'll learn how to evaluate model performance, identify and address issues, and harness recent advancements in deep learning and generative modeling using PyTorch and scikit-learn. Your journey to developing high quality models in practice will also encompass causal and human-in-the-loop modeling and machine learning explainability. With hands-on examples and clear explanations, you'll develop the skills to deliver impactful solutions across domains such as healthcare, finance, and e-commerce.What you will learn Enhance data quality and eliminate data flaws Effectively assess and improve the performance of your models Develop and optimize deep learning models with PyTorch Mitigate biases to ensure fairness Understand explainability techniques to improve model qualities Use test-driven modeling for data processing and modeling improvement Explore techniques to bring reliable models to production Discover the benefits of causal and human-in-the-loop modeling Who this book is forThis book is for data scientists, analysts, machine learning engineers, Python developers, and students looking to build reliable, high-performance, and explainable machine learning models for production across diverse industrial applications. Fundamental Python skills are all you need to dive into the concepts and practical examples covered. Whether you're new to machine learning or an experienced practitioner, this book offers a breadth of knowledge and practical insights to elevate your modeling skills.
Author: Theo von Taane
Author: Theo von Taane
Author: Joe Byerly
Author: Shih-Chia Huang
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Author: Walter James Greenleaf
Author: 
Author: Debra J. Smith
Author: Glen O. Gabbard
Author: 
Author: Ali Madani