The book consists of a selection of the forms of the axiom of choice which appeared in the literature together with additional forms which were obtained in the process of writing the book.
Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandasKey FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook DescriptionExploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset.
Get hands-on with deploying and managing your database services to provide scalable and high-speed data access on CockroachDBKey FeaturesGain insights into CockroachDB and build highly reliable cloud-native applicationsExplore the power of a scalable and highly available cloud-native SQL database to distribute data and workloads automaticallyBuild high-speed database services using CockroachDB and troubleshoot performance issuesBook DescriptionGetting Started with CockroachDB will introduce you to the inner workings of CockroachDB and help you to understand how it provides faster access to distributed data through a SQL interface.
Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasksKey FeaturesExplore efficient Reinforcement Learning algorithms and code them using TensorFlow and PythonTrain Reinforcement Learning agents for problems, ranging from computer games to autonomous driving.
Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applicationsKey FeaturesDiscover the new features introduced in Elasticsearch 7Explore techniques for distributed search, indexing, and clusteringGain hands-on knowledge of implementing Elasticsearch for your enterpriseBook DescriptionElasticsearch is one of the most popular tools for distributed search and analytics.
Build, design and improve advanced business intelligence solutions using Tableau's latest features, including Tableau Prep, Tableau Hyper, and Tableau ServerKey FeaturesMaster new features in Tableau 2019.
Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV.
Learn how to make the right decisions for your business with the help of Python recipes and the expertise of data leadersKey FeaturesLearn and practice various clustering techniques to gather market insights Explore real-life use cases from the business world to contextualize your learningWork your way through practical recipes that will reinforce what you have learnedBook DescriptionOne of the most valuable contributions of data science is toward helping businesses make the right decisions.
Re-Inventing the Book: Challenges from the Past for the Publishing Industry chronicles the significant changes that have taken place in the publishing industry in the past few decades and how they have altered the publishing value chain and the structure of the industry itself.
Religion in the Americas explores the fluid, dynamic, and complex nature of religion across Latin America and its diasporic communities in the United States.
Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key FeaturesA step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZA modern, practical and computational approach to Bayesian statistical modelingA tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.
Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsKey FeaturesDelve into machine learning with this comprehensive guide to scikit-learn and scientific PythonMaster the art of data-driven problem-solving with hands-on examplesFoster your theoretical and practical knowledge of supervised and unsupervised machine learning algorithmsBook DescriptionMachine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners.
Find, explore, and extract big data to transform into actionable insightsKey FeaturesPerform end-to-end data analysis-from exploration to visualizationReal-world examples, tasks, and interview queries to be a proficient data scientistUnderstand how SQL is used for big data processing using HiveQL and SparkSQLBook DescriptionSQL Server is a relational database management system that enables you to cover end-to-end data science processes using various inbuilt services and features.
An expert guide to implementing fast, secure, and scalable decentralized applications that work with thousands of users in real timeKey FeaturesImplement advanced features of the Ethereum network to build powerful decentralized applicationsBuild smart contracts on different domains using the programming techniques of Solidity and VyperExplore the architecture of Ethereum network to understand advanced use cases of blockchain development Book DescriptionEthereum is one of the commonly used platforms for building blockchain applications.
A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial IntelligenceKey FeaturesLearn to build and run a big data application with sample codeExplore examples to implement activities that a big data architect performsUse Machine Learning and AI for structured and unstructured dataBook DescriptionThe big data architects are the "e;masters"e; of data, and hold high value in today's market.
Learn to effectively manage data and execute data science projects from start to finish using PythonKey FeaturesUnderstand and utilize data science tools in Python, such as specialized machine learning algorithms and statistical modelingBuild a strong data science foundation with the best data science tools available in PythonAdd value to yourself, your organization, and society by extracting actionable insights from raw dataBook DescriptionPractical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.
This authoritative and practical introduction to solution architecture is suitable for new entrants to the field but also of benefit to experienced professionals wishing to consolidate their knowledge and skills.
Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problemsKey FeaturesGain a comprehensive overview of different machine learning techniquesExplore various methods for selecting a particular algorithmImplement a machine learning project from problem definition through to the final modelBook DescriptionWith huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed.
Combine popular machine learning techniques to create ensemble models using PythonKey FeaturesImplement ensemble models using algorithms such as random forests and AdaBoostApply boosting, bagging, and stacking ensemble methods to improve the prediction accuracy of your model Explore real-world data sets and practical examples coded in scikit-learn and KerasBook DescriptionEnsembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power.
Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python's most popular TensorFlow framework.
