38871Machine learning
Contents: 1. Introduction; 2. Concept learning and the general-to-specific ordering; 3. Decision tree learning; 4. Artificial neural networks; 5. Evaluating hypotheses; 6. Bayesian learning; 7. Computational learning theory; 8. Instance-based learning; 9. Genetic algorithms; 10. Learning sets of rules; 11. Analytical learning; 12. Combining inductive and analytical learning; 13. Reinforcement learning.
38872Machine learning : a probabilistic perspective
Including contesnts: Probability; Generative models for discrete data; Gaussian models; Bayesian statistics; Frequentist statistics; Linear regression; Logistic regression; Generalized linear models and the exponential family; Directed graphical models (Bayes nets); Mixture models and the EM algorithm; Latent linear models; Sparse linear models; Kernels; Gaussian processes; Adaptive basis function models; Markov and hidden Markov models; State space models; Undirected graphical models (Markov random fields); Exact inference for graphical models; Variational inference; More variational inference.
38873Machine learning : hands-on for developers and technical professionals
Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals.
38874Machine learning : the new AI
1. Why we are interested in machine learning; 2. Machine learning, statistics and data analytics; 3. Pattern recognition; 4. Neural networks and deep learning; 5. Learning clusters and recommendations; 6. Learning to take actions; 7. Where do we go from here?.
38875Machine learning in the aws cloud : add intelligence to applications with amazon sagemaker and amazon rekognition
Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services.
38876Machine learning system design interview
Machine learning system design interviews are the most difficult to tackle of all technical interview questions. This book provides a reliable strategy and knowledge base for approaching a broad range of ML system design questions. It provides a step-by-step framework for tackling an ML system design question. It includes many real-world examples to illustrate the systematic approach, with detailed steps you can follow.
38877Machine learning with PySpark
This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along with natural language processing and recommender systems using PySpark. Machine Learning with PySpark shows you how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forest. You’ll also see unsupervised machine learning models such as K-means and hierarchical clustering.
38878Machine learning-based geospatial modeling of urban land surface temperature using topographical features and urban morphology = Mô hình hóa không gian địa lý dựa trên máy học về nhiệt độ bề mặt đô thị sử dụng các đặc điểm địa hình và hình thái đô thị
The factors of green space density and waterbody density have apparent negative correlations with the predicted output, demonstrating their cooling effects in the study area. The findings in this study provide more insights into the spatial distribution of LST in Hue City, helping lanners in urban planning and mitigating the negative effects of urban heat island phenomenon.
38879Machine translation
This volume in the MIT Press Essential Knowledge series offers a concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and market potential. The main approaches are presented from a largely historical perspective and in an intuitive manner, allowing the reader to understand the main principles without knowing the mathematical details.
38880Machinery's handbook : 30th edition
The 30th edition of the “Bible of the Metalworking Industries” contains major revisions of existing content, as well as new material on a variety of topics. It is the essential reference for mechanical, manufacturing, and industrial engineers, designers, draftsmen, toolmakers, machinists, engineering and technology students, and the serious home hobbyist.