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Author: Alberto Boschetti
Publisher: Packt Publishing Ltd
ISBN: 1786462834
Category : Computers
Languages : en
Pages : 373
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Book Description
Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Author: Alberto Boschetti
Publisher: Packt Publishing Ltd
ISBN: 1786462834
Category : Computers
Languages : en
Pages : 373
Get Book Here
Book Description
Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Author: Graham J. Williams
Publisher: CRC Press
ISBN: 1351647490
Category : Business & Economics
Languages : en
Pages : 295
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Book Description
The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data. Building on over thirty years’ experience in teaching and practising data science, the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets. The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data, the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.
Author: Catherine Delves-Yates
Publisher: SAGE
ISBN: 1526451557
Category : Medical
Languages : en
Pages : 1228
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Book Description
Essentials of Nursing Practice introduces the core topics and essential information that nursing students, in all four fields, will need to master during the first year of a nursing degree. It expertly brings together insight from over fifty experienced lecturers, nurses and healthcare professionals, along with contributions from student nurses, to deliver the most complete guide to successfully becoming a registered nurse. Key features: A clear, full-colour, effective learning design aimed to help students understand the core theory, skills and knowledge, and how this can be applied in practice through holistic, person-centred nursing. Covers professional issues such as ethics, law, accountability, core academic skills like writing and completing assignments, and fundamental clinical skills such as pain management and medicines administration. Includes interactive activities such as critical thinking, reflection and ‘what’s the evidence’ boxes. Real-life ‘voices’ and experiences from patients, students and practitioners are integrated throughout. Addresses the transition to the new NMC Standards of Proficiency with a new tool developed for educators mapping the content of the book to both the existing and new standards. Readers get free 24/7 access to videos, case studies, journal articles, quizzes and multiple choice questions at the click of a button, by downloading the interactive eBook version of the text. (Redemption code and instructions inside the book)
Author: Alberto Boschetti
Publisher: Packt Publishing Ltd
ISBN: 1789531896
Category : Computers
Languages : en
Pages : 466
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Book Description
Gain useful insights from your data using popular data science tools Key FeaturesA one-stop guide to Python libraries such as pandas and NumPyComprehensive coverage of data science operations such as data cleaning and data manipulationChoose scalable learning algorithms for your data science tasksBook Description Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You’ll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost. By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users What you will learnSet up your data science toolbox on Windows, Mac, and LinuxUse the core machine learning methods offered by the scikit-learn libraryManipulate, fix, and explore data to solve data science problemsLearn advanced explorative and manipulative techniques to solve data operationsOptimize your machine learning models for optimized performanceExplore and cluster graphs, taking advantage of interconnections and links in your dataWho this book is for If you’re a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book.
Author: NSCA -National Strength & Conditioning Association
Publisher: Human Kinetics Publishers
ISBN: 1492593354
Category : Exercise
Languages : en
Pages : 576
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Book Description
NSCA's Essentials of Sport Science provides the most contemporary and comprehensive overview of the field of sport science and the role of the sport scientist. It is a primary preparation resource for the Certified Performance and Sport Scientist (CPSS) certification exam.
Author: American Academy of Orthopaedic Surgeons (AAOS),
Publisher: Jones & Bartlett Learning
ISBN: 128425674X
Category : Medical
Languages : en
Pages : 3079
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Book Description
The Ninth Edition teaches students the technical skills required of today’s paramedic while emphasizing other important professional attributes, including critical thinking, empathy, teamwork, communication, problem solving, and personal well-being.
Author: John Sheppard
Publisher: World Scientific
ISBN: 9811225338
Category : Cooking
Languages : en
Pages : 212
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Book Description
Written as an introduction to the science of brewing and beer fermentation, this book provides an up-to-date overview of the science behind the various operations involved in the making of beer. Various subject-matter experts contribute their knowledge and unique perspectives on the most important topics in brewing, appealing to all readers wishing to expand their understanding of the chemical, microbiological and business aspects of brewery operation, with particular emphasis on the craft industry.
Author: Rosemary Sherrington
Publisher: Nelson Thornes
ISBN: 9780748764891
Category : Education
Languages : en
Pages : 148
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Book Description
Devised to help teachers of primary science in schools. This title offers a two-year age band structure, correlation to the QCA Scheme of Work, and recommended teaching times. The Overview page is to introduce the themes in the unit. Review page is meant to assess learning. The Teacher Resource Books contain structured lesson plans.
Author:
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 1118
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Book Description
Some issues are accompanied by a CD-ROM on a selected topic.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309214459
Category : Education
Languages : en
Pages : 400
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Book Description
Science, engineering, and technology permeate nearly every facet of modern life and hold the key to solving many of humanity's most pressing current and future challenges. The United States' position in the global economy is declining, in part because U.S. workers lack fundamental knowledge in these fields. To address the critical issues of U.S. competitiveness and to better prepare the workforce, A Framework for K-12 Science Education proposes a new approach to K-12 science education that will capture students' interest and provide them with the necessary foundational knowledge in the field. A Framework for K-12 Science Education outlines a broad set of expectations for students in science and engineering in grades K-12. These expectations will inform the development of new standards for K-12 science education and, subsequently, revisions to curriculum, instruction, assessment, and professional development for educators. This book identifies three dimensions that convey the core ideas and practices around which science and engineering education in these grades should be built. These three dimensions are: crosscutting concepts that unify the study of science through their common application across science and engineering; scientific and engineering practices; and disciplinary core ideas in the physical sciences, life sciences, and earth and space sciences and for engineering, technology, and the applications of science. The overarching goal is for all high school graduates to have sufficient knowledge of science and engineering to engage in public discussions on science-related issues, be careful consumers of scientific and technical information, and enter the careers of their choice. A Framework for K-12 Science Education is the first step in a process that can inform state-level decisions and achieve a research-grounded basis for improving science instruction and learning across the country. The book will guide standards developers, teachers, curriculum designers, assessment developers, state and district science administrators, and educators who teach science in informal environments.
