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Bioremediation --- Technique.

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Molecular biology --- Technique.

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A perfect guide to speed up the predicting power of machine learning algorithms About This Book Design, discover, and create dynamic, efficient features for your machine learning application Understand your data in-depth and derive astonishing data insights with the help of this Guide Grasp powerful feature-engineering techniques and build machine learning systems Who This Book Is For If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python scripting would be enough to get started with this book. What You Will Learn Identify and leverage different feature types Clean features in data to improve predictive power Understand why and how to perform feature selection, and model error analysis Leverage domain knowledge to construct new features Deliver features based on mathematical insights Use machine-learning algorithms to construct features Master feature engineering and optimization Harness feature engineering for real world applications through a structured case study In Detail Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. Style and approach This step-by-step guide with use cases, examples, and illustrations will help you master the concepts of feature engineering. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world. Downloading the example code for this book...

Machine learning --- Technique.

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Escrito inteiramente em inglês, o presente livro foi concebido por especialistas em morfologia pertencentes à Central Brasileira de Estudos em Morfologia de Carrapatos (BCSTM) da Universidade Estadual Paulista, campus de Rio Claro (SP). O objetivo é esclarecer a morfo-histologia do carrapato, por meio de uma compilação de estudos sobre técnicas histológicas e histoquímicas; biologia, morfologia e taxonomia das principais espécies de carrapatos estudadas histologicamente; histologia de órgãos de carrapato, técnicas histológicas aplicadas para analisar os efeitos acaricidas em órgãos de carrapatos; e novas perspectivas sobre glândulas salivares de carrapatos para seleção de compostos com propriedades farmacológicas. Os capítulos são complementados por ilustrações.

Histology --- Technique. --- Biology, life sciences

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Innovation is often presented as one of the main catalysts for more sustainable and inclusive development. In the agricultural and food sectors, innovation is characterized not only by specificities arising from its relationship to nature, but also from the wide diversity of its stakeholders, ranging from farmers to consumers, and including intermediaries such as the research community and advisory services. Innovation emerges from interactions between these actors, who mobilize resources and produce knowledge in collaborative mechanisms in order to generate changes. It encompasses domains as varied as production practices, market organization, and eating habits. Innovation is closely tied to major development challenges in its various forms: agroecological innovation, social innovation, territorial innovation, etc. This book casts a look at innovation in agricultural and food systems. It focuses in particular on supporting innovation, by examining methods and organizations, and on evaluating innovation using different yardsticks. The book is based on reflections and research originating from various scientific disciplines, on fieldwork carried out both in France and in many countries of the Global South, and finally on the experiences gained by accompanying and supporting innovative actors. It combines theoretical contributions on innovation with iconic case studies to illustrate its observations and discussions. This book is intended for teachers, professionals, students, and researchers.

Agricultural science --- agriculture --- alimentation --- conseil technique