PDF Andrew Learns about Engineers Download
- Author: Tiffany Obeng
- Publisher:
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- Languages : en
- Pages : 38
Childrens book about engineers
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This book introduces the concept of "the engineering process" as a way to solve problems in the real world in a fun, simple way to boost STEAM knowledge! Stem books for kids 3-5.Teach kids how to think like an engineer and apply the engineering process to problem-solving. The process explained in this book will encourage try and solve everyday problems using engineering. The purpose is to inspire more little Engineers to build a better world. This children's picture book shows kids just how cool it is to be an Engineer and use their knowledge of engineering to build cool things that solve problems and move society into the future. The book explains the various types of engineers and what it takes to become one. It shows real-world solutions that we use every day created by Engineers. Throughout the book, a diverse team of Kid Engineers solves the problem of how humans can exploring other planets and survive long distances in space. The team decides to solve the problem by a building Robot to travel through space to explore other planets then come back and tell them what he found. Its a great mix of facts and story format to reinforce stem knowledge.
Looking for a children's book about lawyers? This is it! It's "Take Your Kid to Work Day" and Andrew is beyond excited to go to work with Mama until he realizes that he does not know what Mama does for work. "I am a lawyer or what some call an attorney," begins the exploration of the wonderful world of lawyers. Andrew Learns about Lawyers, the third book in the Andrew Career Day book series, is a great book and beginner career resource to introduce young children (ages 4-8) to the career of a lawyer. Complete with phonetic assistance, an easy reader glossary, and diverse and inclusive images and images of legal pioneers (think Ruth Bader Ginsburg or Thurgood Marshall!), your child will begin thinking of a possible career as a lawyer and be in awe of the lawyers in their life. Andrew Learns about Lawyers shows how special and important being a lawyer is, which makes it the perfect gift for lawyers, gift for law students, and gift for recent law graduates! Andrew's Career Day books are a great way to promote learning and awareness of the featured profession by engaging both kids and adults with simple and slightly complex words, and beautifully colorful illustrations. These rhyming career exploration books are perfect for curious sons and daughters as they provide just enough information in an easy to follow and interesting way. By the end of each book, your child will be inspired to learn more about the career and the special pioneers of the field.
Sam is a curious, 8-year old girl in a family of Engineers. Join her journey to learn about different types of Engineers and how they design the products that we use everyday. This is the first STEM / STEAM book in a series designed for children ages 5-10 to better understand and appreciate different engineering disciplines such as computer, software, environmental, mechanical, aerospace and electrical engineering. It also encourages young girls to explore STEM.
New York Times Bestseller Rosie may seem quiet during the day, but at night she’s a brilliant inventor of gizmos and gadgets who dreams of becoming a great engineer. When her great-great-aunt Rose (Rosie the Riveter) comes for a visit and mentions her one unfinished goal—to fly—Rosie sets to work building a contraption to make her aunt’s dream come true. But when her contraption doesn’t fly but rather hovers for a moment and then crashes, Rosie deems the invention a failure. On the contrary, Aunt Rose insists that Rosie’s contraption was a raging success: you can only truly fail, she explains, if you quit. From the powerhouse author-illustrator team of Iggy Peck, Architect comes Rosie Revere, Engineer, another charming, witty picture book about believing in yourself and pursuing your passion. Ada Twist, Scientist, the companion picture book featuring the next kid from Iggy Peck's class, is available in September 2016.!--?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" /-- Praise for Rosie Revere, Engineer"Comically detailed mixed-media illustrations that keep the mood light and emphasize Rosie’s creativity at every turn."—Publishers Weekly "The detritus of Rosie’s collections is fascinating, from broken dolls and stuffed animals to nails, tools, pencils, old lamps and possibly an erector set. And cheddar-cheese spray." —Kirkus Reviews "This celebration of creativity and perseverance is told through rhyming text, which gives momentum and steady pacing to a story, consistent with the celebration of its heroine, Rosie. She’s an imaginative thinker who hides her light under a bushel (well, really, the bed) after being laughed at for one of her inventions." —Booklist Award 2013 Parents' Choice Award - GOLD 2014 Amelia Bloomer Project List ReadBoston's Best Read Aloud Book
Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments Key Features Explore hyperparameter optimization and model management tools Learn object-oriented programming and functional programming in Python to build your own ML libraries and packages Explore key ML engineering patterns like microservices and the Extract Transform Machine Learn (ETML) pattern with use cases Book DescriptionMachine learning engineering is a thriving discipline at the interface of software development and machine learning. This book will help developers working with machine learning and Python to put their knowledge to work and create high-quality machine learning products and services. Machine Learning Engineering with Python takes a hands-on approach to help you get to grips with essential technical concepts, implementation patterns, and development methodologies to have you up and running in no time. You'll begin by understanding key steps of the machine learning development life cycle before moving on to practical illustrations and getting to grips with building and deploying robust machine learning solutions. As you advance, you'll explore how to create your own toolsets for training and deployment across all your projects in a consistent way. The book will also help you get hands-on with deployment architectures and discover methods for scaling up your solutions while building a solid understanding of how to use cloud-based tools effectively. Finally, you'll work through examples to help you solve typical business problems. By the end of this book, you'll be able to build end-to-end machine learning services using a variety of techniques and design your own processes for consistently performant machine learning engineering.What you will learn Find out what an effective ML engineering process looks like Uncover options for automating training and deployment and learn how to use them Discover how to build your own wrapper libraries for encapsulating your data science and machine learning logic and solutions Understand what aspects of software engineering you can bring to machine learning Gain insights into adapting software engineering for machine learning using appropriate cloud technologies Perform hyperparameter tuning in a relatively automated way Who this book is for This book is for machine learning engineers, data scientists, and software developers who want to build robust software solutions with machine learning components. If you're someone who manages or wants to understand the production life cycle of these systems, you'll find this book useful. Intermediate-level knowledge of Python is necessary.
The most comprehensive book on the engineering aspects of building reliable AI systems. "If you intend to use machine learning to solve business problems at scale, I'm delighted you got your hands on this book." -Cassie Kozyrkov, Chief Decision Scientist at Google "Foundational work about the reality of building machine learning models in production." -Karolis Urbonas, Head of Machine Learning and Science at Amazon