Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applicationsKey FeaturesBuild independent machine learning (ML) systems leveraging the best features of R 3.
Build a strong foundation of machine learning algorithms in 7 daysKey FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7 most widely used machine learning algorithms within a weekKnow when and where to apply data science algorithms using this guideBook DescriptionMachine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data.
First place winner in Educational Products at the 2021 International Cartographic Conference Maps are ubiquitous, yet maps are not made equally, nor are they read equally.
Get to grips with building reliable, scalable, and maintainable database solutions for enterprises and production databasesKey FeaturesImplement PostgreSQL 13 features to perform end-to-end modern database managementDesign, manage, and build enterprise database solutions using a unique recipe-based approachSolve common and not-so-common challenges faced while working to achieve optimal database performanceBook DescriptionPostgreSQL has become the most advanced open source database on the market.
Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python introduces readers to the foundational concepts of data analysis, cognitive science, and computational intelligence, including AI and Machine Learning.
This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data.
Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise resultsKey FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook DescriptionData Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments.
This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future.
As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease.
Learn the ropes of supervised machine learning with R by studying popular real-world use-cases, and understand how it drives object detection in driver less cars, customer churn, and loan default prediction.
Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your dataKey FeaturesIntegrate machine learning with distributed search and analyticsPreprocess and analyze large volumes of search data effortlesslyOperationalize machine learning in a scalable, production-worthy wayBook DescriptionElastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively.
Get up and running with the fundamentals of Bitcoin and blockchainKey FeaturesLearn quick, effective, and easy ways to master blockchain and Bitcoin Understand the impact of decentralization and discover ways to tackle it Explore the future of Bitcoin and blockchain and implement them in a business networkBook DescriptionBlockchain is a distributed database that enables permanent, transparent, and secure storage of data.
Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandasKey FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook DescriptionPython is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries.
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice.
Leverage the power of Python and statistical modeling techniques for building accurate predictive modelsKey FeaturesGet introduced to Python's rich suite of libraries for statistical modelingImplement regression, clustering and train neural networks from scratchIncludes real-world examples on training end-to-end machine learning systems in PythonBook DescriptionPython's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today.
Designed with beginners in mind, this workshop helps you make the most of Python libraries and the Jupyter Notebook's functionality to understand how data science can be applied to solve real-world data problems.
Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction.
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 how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework.
Extend PostgreSQL using PostgreSQL server programming to create, test, debug, and optimize a range of user-defined functions in your favorite programming languageKey FeaturesLearn the concepts of PostgreSQL 11 with lots of real-world datasets and examplesLearn queries, data replication, and database performanceExtend the functionalities of your PostgreSQL instance to suit your organizational needsBook DescriptionPostgreSQL is a rock-solid, scalable, and safe enterprise-level relational database.
This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis.
A practical guide for multivariate statistical techniques-- nowupdated and revised In recent years, innovations in computer technology and statisticalmethodologies have dramatically altered the landscape ofmultivariate data analysis.
Become an expert at using Python for advanced statistical analysis of data using real-world examplesAbout This BookClean, format, and explore data using graphical and numerical summariesLeverage the IPython environment to efficiently analyze data with PythonPacked with easy-to-follow examples to develop advanced computational skills for the analysis of complex dataWho This Book Is ForIf you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you.
Understand data analysis concepts to make accurate decisions based on data using Python programming and Jupyter NotebookKey FeaturesFind out how to use Python code to extract insights from data using real-world examplesWork with structured data and free text sources to answer questions and add value using dataPerform data analysis from scratch with the help of clear explanations for cleaning, transforming, and visualizing dataBook DescriptionData literacy is the ability to read, analyze, work with, and argue using data.
Quickly build and deploy machine learning models without managing infrastructure, and improve productivity using Amazon SageMaker's capabilities such as Amazon SageMaker Studio, Autopilot, Experiments, Debugger, and Model MonitorKey FeaturesBuild, train, and deploy machine learning models quickly using Amazon SageMakerAnalyze, detect, and receive alerts relating to various business problems using machine learning algorithms and techniquesImprove productivity by training and fine-tuning machine learning models in productionBook DescriptionAmazon SageMaker enables you to quickly build, train, and deploy machine learning (ML) models at scale, without managing any infrastructure.
Data Alchemy in the Insurance Industry: The Transformative Power of Big Data Analytics is a groundbreaking work that explores the transformative power of big data analytics within the insurance industry.
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud.
Learn the fundamentals of clean, effective Python coding and build the practical skills to tackle your own software development or data science projectsKey FeaturesBuild key Python skills with engaging development tasks and challenging activitiesImplement useful algorithms and write programs to solve real-world problemsApply Python in realistic data science projects and create simple machine learning modelsBook DescriptionHave you always wanted to learn Python, but never quite known how to start?
Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy.
