Practical Bioinformatics For Beginners: From Raw Sequence Analysis To Machine Learning Applications, Lloyd Wai Yee Low, Martti Tapani Tammi
Автор: Fink, Heather Hedrick, Название: Practical applications in sports nutrition / ISBN: 1284181340 ISBN-13(EAN): 9781284181340 Издательство: NBN International Рейтинг: Цена: 12670.00 р. Наличие на складе: Нет в наличии.
Описание: Every new print copy of Practical Applications in Sports Nutrition, Sixth Edition includes Navigate 2 Premier Access which includes numerous learning tools and study aids including a full eBook, 15 interactive case-study modules, animations, workbook exercises in writable PDF format, and much more. The sixth edition of Practical Applications in Sports Nutrition provides students with the latest sports nutrition information and dietary practices enabling them to assist athletes and fitness enthusiasts in achieving their personal performance goals. The authors provide data and statistics from the latest nutrition research and guidelines to demonstrate effective ways to communicate sports nutrition messages to athletes and outline how to motivate individuals to make permanent behavior change. Early chapters provide an introduction to sports nutrition and give a thorough explanation of macronutrients, micronutrients, and water, and their relation to athletic performance. Later chapters focus on the practical and applied aspects of sports nutrition including behavior change through consultations and weight management. An end-of-text workbook provides readers with an opportunity to apply the information they have learned to various real-world activities. Instructor resources include a test bank with chapter quizzes, mid-term and final (in Navigate 2), Lecture Slides in PowerPoint format, and Instructor's Manual.
Описание: This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics.
Описание: In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few.
Описание: If you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading.
Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language.
That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science.
Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.
The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms,
In manuscript one, Python for Beginners, you will learn:
How to install Python
What are the different Python Data Types and Variables
Basic Operators of Python Language
Data Structures and Functions
Conditional and Loops in Python
And Much More
In manuscript two, Python Advanced Guide, you will master:
Object-Oriented Programming (OOP), Inheritance and Polymorphism
Essential Programming Tools
Exception Handling
Working with Files
And Much More
In manuscript three, Python for Data Analysis, you will learn:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
The 7 Python libraries that make Python one of the best choices for Data Analysis
Pandas, Jupyter and PyTorch
And Much More
In manuscript four, Applications to Data Science, you will understand:
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Neural Networks
Decision Trees
What industries are using data to improve their business with 14 real-world applications
And So Much More
Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding.
Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples.
Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications.
Would you like to know more?Scroll Up and Click the BUY NOW Button to Get Your Copy
Описание: If you want to learn more about Data Science or how to master it with the Python Programming Language Step-by-Step, then keep reading.
Data Science is one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?"
Data Science includes all the different steps that you take with the data: collecting and cleaning them if they come from more than one source, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations.
You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. Some of the topics that we will discuss inside include
-A thorough and simple explanation of data science and the way it works
-Basics of data science and fundamental skills you need to get started
-A blueprint for the most used frameworks for Python data science
-How to process and understand the data and design your own projects
-What data science is all about and why so many companies are using it to give them a competitive edge.
-Why Python and how to use it to implement Data Science
-What is the intersection between Machine Learning and Data Science and how to combine them
-Functions and Modules in Python
-Data Aggregation and Group Operations
-Interaction with databases and data in the cloud
-And Much More
Even if you have never implemented Data Science techniques, learning them is easier than it looks. You just need the right guidance. And Python Data Science provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn, the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications.
Would You Like To Know More?
Scroll up and click on the BUY NOW button to get your copy now
Описание: If you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading.
Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language.
That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science.
Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.
The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms,
In manuscript one, Python for Beginners, you will learn:
How to install Python
What are the different Python Data Types and Variables
Basic Operators of Python Language
Data Structures and Functions
Conditional and Loops in Python
And Much More
In manuscript two, Python Advanced Guide, you will master:
Object-Oriented Programming (OOP), Inheritance and Polymorphism
Essential Programming Tools
Exception Handling
Working with Files
And Much More
In manuscript three, Python for Data Analysis, you will learn:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
The 7 Python libraries that make Python one of the best choices for Data Analysis
Pandas, Jupyter and PyTorch
And Much More
In manuscript four, Applications to Data Science, you will understand:
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Neural Networks
Decision Trees
What industries are using data to improve their business with 14 real-world applications
And So Much More
Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding.
Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples.
Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications.
Would you like to know more?Scroll Up and Click the BUY NOW Button to Get Your Copy
Описание: This book takes the novel approach to cover both the sequence and structure analysis of proteins in one volume and from an algorithmic perspective. Key features of the book include:* Provides a comprehensive introduction to the analysis of protein sequence and structure analysis.
Описание: Building Data-Driven Applications with Danfo.js enables you to manipulate, analyze, and wrangle structured data in JavaScript environments. If you`re a JavaScript developer working with data, this book will serve as a practical guide to using Danfo.js.
Описание: Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘14 contributes to this effort promoting this fruitful interaction. PACBB'14 technical program included 34 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference promotes the interaction of scientists from diverse research groups and with a distinct background such as computer scientists, mathematicians or biologists.
Описание: This proceedings presents recent practical applications of Computational Biology and Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences.
Описание: This book highlights the latest research on practical applications of computational biology and bioinformatics, and addresses emerging experimental and sequencing techniques that are posing new challenges for bioinformatics and computational biology.
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