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Please check the ISBN that your instructor provided. If the ISBN-13 does not match this product (9781285766249) this may not be the correct product. In some cases, you may also require a course code from your Instructor.

The top-rated diet-analysis software and a must-have for success in your nutrition course, DIET ANALYSIS PLUS enables you to track your diet and physical activity, and analyze the nutritional value of the food you eat! Diet Analysis Plus includes a 20,000+ food database, custom food and recipe features, the latest Dietary References, as well as your goal and actual percentages of essential nutrients, vitamins, and minerals. New features include enhanced search functionality with filter option, and resources tab with helpful information. You can create your own personal profile based on height, weight, age, sex, and activity level-AND use this information to adjust your diet and gain a better understanding of how nutrition relates to your personal health goals. T

• ISBN: 9781285766249
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Over 60 practical recipes on data exploration and analysisAbout This BookClean dirty data, extract accurate information, and explore the relationships between variablesForecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learnFind and extract the most important features from your dataset using the most efficient Python librariesWho This Book Is ForIf you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so.What You Will LearnRead, clean, transform, and store your data usng Pandas and OpenRefineUnderstand your data and explore the relationships between variables using Pandas and D3.jsExplore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, m

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As its title suggests, this innovative book has been written for life scientists needing to analyse their data sets, and programmers, wanting a better understanding of the types of experimental images life scientists investigate on a regular basis. Each chapter presents one self-contained biomedical experiment to be analysed. Part I of the book presents its two basic ingredients: essential concepts of image analysis and Matlab. In Part II, algorithms and techniques are shown as series of ‘recipes’ or solved examples that show how specific techniques are applied to a biomedical experiments like Western Blots, Histology, Scratch Wound Assays and Fluoresence. Each recipe begins with simple techniques that gradually advance in complexity. Part III presents some advanced techniques for the generation of publication quality figures. The book does not assume any computational or mathematical expertise.

A practical, clearly-written introduction to biomedical image analysis

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