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Author: Sally Fincher
Publisher: Springer Science & Business Media
ISBN: 1447137000
Category : Business & Economics
Languages : en
Pages : 273
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Book Description
Ninety percent of any Computing Science academic staff are involved with project work at some stage of their working life. Often they have no previous experience of how to handle it, and there are no written guidelines or reference books at the moment. Knowledge and practical experiences are often only disseminated from one institution to another when staff change jobs. This book is the first reference work to fill that gap in the market. It will be of use to lecturers and course designers who want to improve their handling of project work in specific courses, and to department heads and deans who want to learn about overall strategic issues and experiences from other institutions.
Author: Sally Fincher
Publisher: Springer Science & Business Media
ISBN: 1447137000
Category : Business & Economics
Languages : en
Pages : 273
Get Book Here
Book Description
Ninety percent of any Computing Science academic staff are involved with project work at some stage of their working life. Often they have no previous experience of how to handle it, and there are no written guidelines or reference books at the moment. Knowledge and practical experiences are often only disseminated from one institution to another when staff change jobs. This book is the first reference work to fill that gap in the market. It will be of use to lecturers and course designers who want to improve their handling of project work in specific courses, and to department heads and deans who want to learn about overall strategic issues and experiences from other institutions.
Author: Mikael Berndtsson
Publisher: Springer Science & Business Media
ISBN: 1447138465
Category : Education
Languages : en
Pages : 155
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Book Description
Written in concise language this book is for any student who is about to undertake a final year undergraduate or MSc project. It takes them step-by-step through all the important stages of the process, from initial planning to completion. It tells them everything they need to know about key issues such as: How to formulate a suitable problem, Which research method to use, Developing an appropriate structure for the written report, Project focus, and Quality assurance. The book aims to demystify the whole process, making it invaluable for any MSc student.
Author: Mikael Berndtsson
Publisher: Springer Science & Business Media
ISBN: 1848000081
Category : Computers
Languages : en
Pages : 165
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Book Description
You’re a computing or information student with a huge mountain to climb – that final-year research project. Don’t worry, because with this book guardian angels are at hand, in the form of four brilliant academics who will guide you through the process. The book provides you with all the tools necessary to successfully complete a final year research project. Based on an approach that has been tried and tested on over 500 projects, it offers a simple step-by-step guide to the key processes involved. Not only that, but the book also contains lots of useful information for supervisors and examiners including guidelines on how to review a final year project.
Author: Jane Margolis
Publisher: MIT Press
ISBN: 0262533464
Category : Education
Languages : en
Pages : 245
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Book Description
Why so few African American and Latino/a students study computer science: updated edition of a book that reveals the dynamics of inequality in American schools. The number of African Americans and Latino/as receiving undergraduate and advanced degrees in computer science is disproportionately low. And relatively few African American and Latino/a high school students receive the kind of institutional encouragement, educational opportunities, and preparation needed for them to choose computer science as a field of study and profession. In Stuck in the Shallow End, Jane Margolis and coauthors look at the daily experiences of students and teachers in three Los Angeles public high schools: an overcrowded urban high school, a math and science magnet school, and a well-funded school in an affluent neighborhood. They find an insidious “virtual segregation” that maintains inequality. The race gap in computer science, Margolis discovers, is one example of the way students of color are denied a wide range of occupational and educational futures. Stuck in the Shallow End is a story of how inequality is reproduced in America—and how students and teachers, given the necessary tools, can change the system. Since the 2008 publication of Stuck in the Shallow End, the book has found an eager audience among teachers, school administrators, and academics. This updated edition offers a new preface detailing the progress in making computer science accessible to all, a new postscript, and discussion questions (coauthored by Jane Margolis and Joanna Goode).
Author: Thomas J. Manning
Publisher: Bentham Science Publishers
ISBN: 1608051935
Category : Science
Languages : en
Pages : 243
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Book Description
This e-book is a collection of exercises designed for students studying chemistry courses at a high school or undergraduate level. The e-book contains 24 chapters each containing various activities employing applications such as MS excel (spreadsheets) and Spartan (computational modeling). Each project is explained in a simple, easy-to-understand manner. The content within this book is suitable as a guide for both teachers and students and each chapter is supplemented with practice guidelines and exercises. Computer Based Projects for a Chemistry Curriculum therefore serves to bring computer based learning – a much needed addition in line with modern educational trends – to the chemistry classroom.
Author: Randy Sarafan
Publisher: Workman Publishing
ISBN: 0761152431
Category : Crafts & Hobbies
Languages : en
Pages : 273
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Book Description
Presents step-by-step instructions for repurposing a variety of electronic appliances and equipment, including computers, cell phones, and scanners, into other items.
Author: Scott H. Young
Publisher: HarperCollins
ISBN: 0062852744
Category : Business & Economics
Languages : en
Pages : 278
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Book Description
Now a Wall Street Journal bestseller. Learn a new talent, stay relevant, reinvent yourself, and adapt to whatever the workplace throws your way. Ultralearning offers nine principles to master hard skills quickly. This is the essential guide to future-proof your career and maximize your competitive advantage through self-education. In these tumultuous times of economic and technological change, staying ahead depends on continual self-education—a lifelong mastery of fresh ideas, subjects, and skills. If you want to accomplish more and stand apart from everyone else, you need to become an ultralearner. The challenge of learning new skills is that you think you already know how best to learn, as you did as a student, so you rerun old routines and old ways of solving problems. To counter that, Ultralearning offers powerful strategies to break you out of those mental ruts and introduces new training methods to help you push through to higher levels of retention. Scott H. Young incorporates the latest research about the most effective learning methods and the stories of other ultralearners like himself—among them Benjamin Franklin, chess grandmaster Judit Polgár, and Nobel laureate physicist Richard Feynman, as well as a host of others, such as little-known modern polymath Nigel Richards, who won the French World Scrabble Championship—without knowing French. Young documents the methods he and others have used to acquire knowledge and shows that, far from being an obscure skill limited to aggressive autodidacts, ultralearning is a powerful tool anyone can use to improve their career, studies, and life. Ultralearning explores this fascinating subculture, shares a proven framework for a successful ultralearning project, and offers insights into how you can organize and exe - cute a plan to learn anything deeply and quickly, without teachers or budget-busting tuition costs. Whether the goal is to be fluent in a language (or ten languages), earn the equivalent of a college degree in a fraction of the time, or master multiple tools to build a product or business from the ground up, the principles in Ultralearning will guide you to success.
Author: Gayle Laakmann McDowell
Publisher: CreateSpace
ISBN: 9781466208681
Category : Computer programmers
Languages : en
Pages : 0
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Book Description
Now in the 5th edition, Cracking the Coding Interview gives you the interview preparation you need to get the top software developer jobs. This book provides: 150 Programming Interview Questions and Solutions: From binary trees to binary search, this list of 150 questions includes the most common and most useful questions in data structures, algorithms, and knowledge based questions. 5 Algorithm Approaches: Stop being blind-sided by tough algorithm questions, and learn these five approaches to tackle the trickiest problems. Behind the Scenes of the interview processes at Google, Amazon, Microsoft, Facebook, Yahoo, and Apple: Learn what really goes on during your interview day and how decisions get made. Ten Mistakes Candidates Make -- And How to Avoid Them: Don't lose your dream job by making these common mistakes. Learn what many candidates do wrong, and how to avoid these issues. Steps to Prepare for Behavioral and Technical Questions: Stop meandering through an endless set of questions, while missing some of the most important preparation techniques. Follow these steps to more thoroughly prepare in less time.
Author: Stephen Klosterman
Publisher: Packt Publishing Ltd
ISBN: 1800569440
Category : Computers
Languages : en
Pages : 433
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Book Description
Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoost Key FeaturesThink critically about data and use it to form and test a hypothesisChoose an appropriate machine learning model and train it on your dataCommunicate data-driven insights with confidence and clarityBook Description If data is the new oil, then machine learning is the drill. As companies gain access to ever-increasing quantities of raw data, the ability to deliver state-of-the-art predictive models that support business decision-making becomes more and more valuable. In this book, you'll work on an end-to-end project based around a realistic data set and split up into bite-sized practical exercises. This creates a case-study approach that simulates the working conditions you'll experience in real-world data science projects. You'll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest. Now in its second edition, this book will take you through the end-to-end process of exploring data and delivering machine learning models. Updated for 2021, this edition includes brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world. By the end of this data science book, you'll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data. What you will learnLoad, explore, and process data using the pandas Python packageUse Matplotlib to create compelling data visualizationsImplement predictive machine learning models with scikit-learnUse lasso and ridge regression to reduce model overfittingEvaluate random forest and logistic regression model performanceDeliver business insights by presenting clear, convincing conclusionsWho this book is for Data Science Projects with Python – Second Edition is for anyone who wants to get started with data science and machine learning. If you're keen to advance your career by using data analysis and predictive modeling to generate business insights, then this book is the perfect place to begin. To quickly grasp the concepts covered, it is recommended that you have basic experience of programming with Python or another similar language, and a general interest in statistics.
Author: David Kopec
Publisher: Simon and Schuster
ISBN: 1638355231
Category : Computers
Languages : en
Pages : 331
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Book Description
"Whether you're a novice or a seasoned professional, there's an Aha! moment in this book for everyone." - James Watson, Adaptive ”Highly recommended to everyone interested in deepening their understanding of Python and practical computer science.” —Daniel Kenney-Jung, MD, University of Minnesota Key Features • Master formal techniques taught in college computer science classes • Connect computer science theory to real-world applications, data, and performance • Prepare for programmer interviews • Recognize the core ideas behind most “new” challenges • Covers Python 3.7 Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book Programming problems that seem new or unique are usually rooted in well-known engineering principles. Classic Computer Science Problems in Python guides you through time-tested scenarios, exercises, and algorithms that will prepare you for the “new” problems you’ll face when you start your next project. In this amazing book, you'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. As you work through examples for web development, machine learning, and more, you'll remember important things you've forgotten and discover classic solutions that will save you hours of time. What You Will Learn • Search algorithms • Common techniques for graphs • Neural networks • Genetic algorithms • Adversarial search • Uses type hints throughout This Book Is Written For For intermediate Python programmers. About The Author David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014), Classic Computer Science Problems in Swift (Manning, 2018), and Classic Computer Science Problems in Java (Manning, 2020) Table of Contents 1. Small problems 2. Search problems 3. Constraint-satisfaction problems 4. Graph problems 5. Genetic algorithms 6. K-means clustering 7. Fairly simple neural networks 8. Adversarial search 9. Miscellaneous problems
