A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis.
Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your dataKey FeaturesA beginner's guide for performing data analysis loaded with numerous rich, practical examplesAccess to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysisDevelop applications in Scala for real-time analysis and machine learning in Apache SparkBook DescriptionEfficient business decisions with an accurate sense of business data helps in delivering better performance across products and services.
Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and KerasKey FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook DescriptionThe explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML).
Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with JupyterKey FeaturesLearn how to use Jupyter 5.
Practical examples with real-world projects in GIS, Remote sensing, Geospatial data management and Analysis using the R programming languageKey FeaturesUnderstand the basics of R and QGIS to work with GIS and remote sensing dataLearn to manage, manipulate, and analyze spatial data using R and QGISApply machine learning algorithms to geospatial data using R and QGISBook DescriptionManaging spatial data has always been challenging and it's getting more complex as the size of data increases.
Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and DeepnetKey FeaturesUnderstand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specific problemImprove models using parameter tuning, feature engineering, and ensemblingApply advanced neural network models such as deep autoencoders and generative adversarial networks (GANs) across different domainsBook DescriptionDeep learning enables efficient and accurate learning from a massive amount of data.
Gain practical insights by exploiting data in your business to build advanced predictive modeling applications Key Features A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Book Description Social Media and the Internet of Things have resulted in an avalanche of data.
With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the webKey FeaturesBuild industry-standard recommender systemsOnly familiarity with Python is requiredNo need to wade through complicated machine learning theory to use this bookBook DescriptionRecommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon.
Build smarter systems by combining artificial intelligence and the Internet of Things-two of the most talked about topics todayKey FeaturesLeverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT dataProcess IoT data and predict outcomes in real time to build smart IoT modelsCover practical case studies on industrial IoT, smart cities, and home automationBook DescriptionThere are many applications that use data science and analytics to gain insights from terabytes of data.
Your hands-on reference guide to developing, training, and optimizing your machine learning modelsKey FeaturesYour guide to learning efficient machine learning processes from scratchExplore expert techniques and hacks for a variety of machine learning conceptsWrite effective code in R, Python, Scala, and Spark to solve all your machine learning problemsBook DescriptionMachine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques.
Explore powerful R packages to create predictive models using ensemble methodsKey FeaturesImplement machine learning algorithms to build ensemble-efficient modelsExplore powerful R packages to create predictive models using ensemble methodsLearn to build ensemble models on large datasets using a practical approachBook DescriptionEnsemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model.
A comprehensive guide to mastering the most advanced Hadoop 3 conceptsKey FeaturesGet to grips with the newly introduced features and capabilities of Hadoop 3Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystemSharpen your Hadoop skills with real-world case studies and codeBook DescriptionApache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data.
Implement real-world decentralized applications using Python, Vyper, Populus, and EthereumKey FeaturesStay up-to-date with everything you need to know about the blockchain ecosystemImplement smart contracts, wallets, and decentralized applications(DApps) using Python librariesGet deeper insights into storing content in a distributed storage platformBook DescriptionBlockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions.
Implement blockchain principles in your choice of domain using Ethereum Key FeaturesBuild permissioned enterprise-grade blockchain applications from scratchImplement Blockchain-as-a-Service to enterprises in terms of deployment and securityAchieve privacy in blockchains using proxy re-encryption algorithmsBook DescriptionThe increasing growth in blockchain use is enormous, and it is changing the way business is done.
This fully revised and updated edition of the bestselling Chief Data Officer's Playbook offers new insights into the role of the CDO and the data environment.
This fully revised and updated edition of the bestselling Chief Data Officer's Playbook offers new insights into the role of the CDO and the data environment.
Harness the power of today's financial technologies -- whether you make 2 trades per year or 2000Tools for the Direct Access Trader shows you how to outfit yourself for success and acquire the speed, functionality, and information access that puts you on the same level as institutional traders - but with maneuverability and flexibility that larger, bulkier traders can't touch.
Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data.
Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form.
Former Wall Street Journal technology reporter Yukari Iwatani Kane delves deep inside Apple in the two years since Steve Jobss death, revealing the tensions and challenges CEO Tim Cook and his team face as they try to sustain Jobss vision and keep the company moving forward.
Leverage the power of Talent Intelligence (TI) to make evidence-informed decisions that drive business performance by using data about people, skills, jobs, business functions and geographies.
In this explosive memoir, a political consultant and technology whistleblower reveals the disturbing truth about the multi-billion-dollar data industry, revealing to the public how companies are getting richer using our personal information and exposing how Cambridge Analytica exploited weaknesses in privacy laws to help elect Donald Trump.
Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization.
Episodes in the history of data, from early modern math problems to today''s inescapable “dataveillance,” that demonstrate the dependence of data on culture.
Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students.
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.
Speed up the design and implementation of deep learning solutions using Apache SparkKey FeaturesExplore the world of distributed deep learning with Apache SparkTrain neural networks with deep learning libraries such as BigDL and TensorFlowDevelop Spark deep learning applications to intelligently handle large and complex datasetsBook DescriptionDeep learning is a subset of machine learning where datasets with several layers of complexity can be processed.
Analytics is the application of mathematical and statistical concepts to large data sets so as to distil insights that offer the owner some options for action and competitive advantage or value.
This book focuses on the recent rise of "e;infodemics"e; as forms of disinformation, misinformation and mal-information saturate contemporary media platforms, shaping public opinion to advance agendas.
Become an expert at using Python for advanced statistical analysis of data using real-world examplesKey Features[*] Clean, format, and explore data using graphical and numerical summaries[*] Leverage the IPython environment to efficiently analyze data with Python[*] Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex dataBook DescriptionPython, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning.
Learn how to bring your data to life with this hands-on guide to visual analytics with TableauKey FeaturesMaster the fundamentals of Tableau Desktop and Tableau PrepLearn how to explore, analyze, and present data to provide business insightsBuild your experience and confidence with hands-on exercises and activitiesBook DescriptionLearning Tableau has never been easier, thanks to this practical introduction to storytelling with data.
