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"Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online"-- "Vast amounts of data present amajor challenge to all thoseworking in computer science, and its many related fields, who need to process and extract value from such data. Machine learning technology is already used to help with this task in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis and robot locomotion. As its usage becomes more widespread, no student should be without the skills taught in this book. Designed for final-year undergraduate and graduate students, this gentle introduction is ideally suited to readers without a solid background in linear algebra and calculus. It covers everything from basic reasoning to advanced techniques in machine learning, and rucially enables students to construct their own models for real-world problems by teaching them what lies behind the methods. Numerous examples and exercises are included in the text. Comprehensive resources for students and instructors are available online"--

519.22 --- 519.22 Statistical theory. Statistical models. Mathematical statistics in general --- Statistical theory. Statistical models. Mathematical statistics in general --- Machine learning. --- Bayesian statistical decision theory. --- Computers --- Computer Vision & Pattern Recognition. --- Bayesian statistical decision theory --- Machine learning --- Learning, Machine --- Artificial intelligence --- Machine theory --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Machine Learning --- COMPUTERS / Computer Vision & Pattern Recognition. --- Apprentissage automatique --- Statistique bayésienne --- Artificial Intelligence --- Bayes Theorem --- Analysis, Bayesian --- Bayesian Approach --- Bayesian Analysis --- Bayesian Forecast --- Bayesian Method --- Bayesian Prediction --- Approach, Bayesian --- Approachs, Bayesian --- Bayesian Approachs --- Forecast, Bayesian --- Method, Bayesian --- Prediction, Bayesian --- Theorem, Bayes --- Computational Intelligence --- AI (Artificial Intelligence) --- Computer Reasoning --- Computer Vision Systems --- Knowledge Acquisition (Computer) --- Knowledge Representation (Computer) --- Machine Intelligence --- Acquisition, Knowledge (Computer) --- Computer Vision System --- Intelligence, Artificial --- Intelligence, Computational --- Intelligence, Machine --- Knowledge Representations (Computer) --- Reasoning, Computer --- Representation, Knowledge (Computer) --- System, Computer Vision --- Systems, Computer Vision --- Vision System, Computer --- Vision Systems, Computer --- Heuristics --- 681.3*I2 --- 681.3*I2 Artificial intelligence. AI --- Artificial intelligence. AI

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Finding a suitable balance of work and family life is not an easy task for parents who face multiple, and potentially conflicting, demands. Childcare policies play a crucial role in helping parents reconcile care and employment-related tasks. But inconsistent or poorly implemented policies can also introduce additional barriers that make it harder for families to arrange and share their responsibilities according to their needs and preferences. This paper quantifies the net cost of purchasing centre-based childcare in OECD countries taking into account a wide range of influences on household budgets, including fees charged by childcare providers as well as childcare-related tax concessions and cash benefits available to parents. Building on these calculations, family resources are evaluated for different employment situations in order to assess the financial trade-offs between work and staying at home. Results are disaggregated to identify the policy features that present barriers to work for parents whose employment decisions are known to be particularly responsive to financial work incentives: lone parents and second earners with young children requiring care.

Social Issues/Migration/Health

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Polynyas are relatively ice-free regions when compared to the areas around them, and have been suggested as being foci for energy transfer between the atmosphere and ocean, ice "factories?, and critical areas with respect to polar ecosystems and biogeochemical cycles. This volume presents an integrated, multidisciplinary review of polynyas in both the Arctic and Antarctic. It emphasizes the meteorology, ice dynamics, oceanography, biological components, chemistry, and modeling of these systems, particularly with respect to their roles in polar processes and distributions. The various interact

Polynyas --- Sea ice. --- Ice --- Ice navigation --- Oceanography --- Icebergs --- Ice clearing --- Polynias --- Sea ice