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❴Read❵ ➫ Signaler un problème Author Adrian Salceanu – It-ural.pro A step by step guide that demonstrates how to build simple to advanced applications through examples in Julia Lang 1x using modern toolsKey FeaturesWork with powerful open source libraries for data wrA step by step guide that demonstrates how to build simple to advanced applications through examples in Julia Lang 1x using modern toolsKey FeaturesWork with powerful open source libraries for data wrangling analysis and visualizationDevelop full featured full stack web applications Learn to perform supervised and unsupervised machine learning and time series analysis with JuliaBook DescriptionJulia is a new programming language that offers a uniue combination of performance and productivity Its powerful features friendly syntax and speed are attracting a growing number of adopters from Python R and Matlab effectively raising the bar for modern general and scientific computingAfter six years in the making Julia has reached version 10 Now is the perfect time to learn it due to its large scale adoption across a wide range of domains including fintech biotech education and AIBeginning with an introduction to the language Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames You will explore functions and the type system methods and multiple dispatch while building a web scraper and a web app Next you'll delve into machine learning where you'll build a books recommender system You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database After metaprogramming the final chapters will discuss dates and time time series analysis visualization and forecastingWe'll close with package development documenting testing and benchmarkingBy the end of the book you will have gained the practical knowledge to build real world applications in JuliaWhat you will learnLeverage Julia's strengths its top packages and main IDE optionsAnalyze and manipulate datasets using Julia and DataFramesWrite complex code while building real life Julia applicationsDevelop and run a web app using Julia and the HTTP packageBuild a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithmsPerform time series data analysis visualization and forecastingWho this book is forData scientists statisticians business analysts and developers who are interested in learning how to use Julia to crunch numbers analyze data and build apps will find this book useful A basic knowledge of programming is assumed Table of ContentsGetting started with Julia ProgrammingCreating Our First Julia AppSetting Up the Wiki GameBuilding the Wiki Game Web CrawlerAdding a Web UI for the Wiki GameImplementing Recommender Sytems with JuliaMachine Learning For Recommender SystemsLeveraging Unsupervised Learning TechniuesWorking with Dates Time and Time SeriesTime Series ForecastingCreating Julia Package.

SA step by step guide that demonstrates how to build simple to advanced applications through examples in Julia Lang 1x using modern toolsKey FeaturesWork with powerful open source libraries for data wrangling analysis and visualizationDevelop full featured full stack web applicationsLearn to perform supervised and unsupervised machine learning and time series analysis with JuliaBook DescriptionJulia is a new programming language that offers a uniue combination of performance and productivity Its powerful features friendly syntax and speed are attracting a growing number of adopters from Python R and Matlab effectively raising the bar for modern general and scientific computingAfter six years in the making Julia has reached version 10 Now is the perfect time to learn it due to its large scale adoption across a wide range of domains including fintech biotech education and AIBeginning with an introduction to the language Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames You will explore functions and the type system methods and multiple dispatch while building a web scraper and a web app Next you'll delve into machine learning where you'll build a books recommender system You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database After metaprogramming the final chapters will discuss dates and time time series analysis visualization and forecastingWe'll close with package development documenting testing and benchmarkingBy the end of the book you will have gained the practical knowledge to build real world applications in JuliaWhat you will learnLeverage Julia's strengths its top packages and main IDE optionsAnalyze and manipulate datasets using Julia and DataFramesWrite complex code while building real life Julia applicationsDevelop and run a web app using Julia and the HTTP packageBuild a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithmsPerform time series data analysis visualization and forecastingWho this book is forData scientists statisticians business analysts and developers who are interested in learning how to use Julia to crunch numbers analyze data and build apps will find this book useful A basic knowledge of programming is assumed Table of ContentsGetting started with Julia ProgrammingCreating Our First Julia AppSetting Up the Wiki GameBuilding the Wiki Game Web CrawlerAdding a Web UI for the Wiki GameImplementing Recommender Sytems with JuliaMachine Learning For Recommender SystemsLeveraging Unsupervised Learning TechniuesWorking with Dates Time and Time SeriesTime Series ForecastingCreating Julia Package.

signaler pdf problème pdf Signaler un kindle Signaler un problème PDF/EPUBSA step by step guide that demonstrates how to build simple to advanced applications through examples in Julia Lang 1x using modern toolsKey FeaturesWork with powerful open source libraries for data wrangling analysis and visualizationDevelop full featured full stack web applicationsLearn to perform supervised and unsupervised machine learning and time series analysis with JuliaBook DescriptionJulia is a new programming language that offers a uniue combination of performance and productivity Its powerful features friendly syntax and speed are attracting a growing number of adopters from Python R and Matlab effectively raising the bar for modern general and scientific computingAfter six years in the making Julia has reached version 10 Now is the perfect time to learn it due to its large scale adoption across a wide range of domains including fintech biotech education and AIBeginning with an introduction to the language Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames You will explore functions and the type system methods and multiple dispatch while building a web scraper and a web app Next you'll delve into machine learning where you'll build a books recommender system You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database After metaprogramming the final chapters will discuss dates and time time series analysis visualization and forecastingWe'll close with package development documenting testing and benchmarkingBy the end of the book you will have gained the practical knowledge to build real world applications in JuliaWhat you will learnLeverage Julia's strengths its top packages and main IDE optionsAnalyze and manipulate datasets using Julia and DataFramesWrite complex code while building real life Julia applicationsDevelop and run a web app using Julia and the HTTP packageBuild a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithmsPerform time series data analysis visualization and forecastingWho this book is forData scientists statisticians business analysts and developers who are interested in learning how to use Julia to crunch numbers analyze data and build apps will find this book useful A basic knowledge of programming is assumed Table of ContentsGetting started with Julia ProgrammingCreating Our First Julia AppSetting Up the Wiki GameBuilding the Wiki Game Web CrawlerAdding a Web UI for the Wiki GameImplementing Recommender Sytems with JuliaMachine Learning For Recommender SystemsLeveraging Unsupervised Learning TechniuesWorking with Dates Time and Time SeriesTime Series ForecastingCreating Julia Package.

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