Matches in SemOpenAlex for { <https://semopenalex.org/work/W3173239227> ?p ?o ?g. }
Showing items 1 to 59 of
59
with 100 items per page.
- W3173239227 abstract "Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, AnacondaAbout This BookUse Anaconda to find solutions for clustering, classification, and linear regressionAnalyze your data efficiently with the most powerful data science stackUse the Anaconda cloud to store, share, and discover projects and librariesWho This Book Is ForHands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It's also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected.What You Will LearnPerform cleaning, sorting, classification, clustering, regression, and dataset modeling using AnacondaUse the package manager conda and discover, install, and use functionally efficient and scalable packagesGet comfortable with heterogeneous data exploration using multiple languages within a projectPerform distributed computing and use Anaconda Accelerate to optimize computational powersDiscover and share packages, notebooks, and environments, and use shared project drives on Anaconda CloudTackle advanced data prediction problemsIn DetailAnaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world.The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You'll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You'll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod.Once you're accustomed to all this, you'll start with operations in data science such as cleaning, sorting, and data classification. You'll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you'll learn how to visualize data using the packages available for Julia, Python, and R.Style and approachThis book is your step-by-step guide full of use cases, examples and illustrations to get you well-versed with the concepts of Anaconda." @default.
- W3173239227 created "2021-07-05" @default.
- W3173239227 creator A5020529629 @default.
- W3173239227 creator A5061151861 @default.
- W3173239227 date "2018-05-31" @default.
- W3173239227 modified "2023-09-27" @default.
- W3173239227 title "Hands-On Data Science with Anaconda" @default.
- W3173239227 hasPublicationYear "2018" @default.
- W3173239227 type Work @default.
- W3173239227 sameAs 3173239227 @default.
- W3173239227 citedByCount "0" @default.
- W3173239227 crossrefType "book" @default.
- W3173239227 hasAuthorship W3173239227A5020529629 @default.
- W3173239227 hasAuthorship W3173239227A5061151861 @default.
- W3173239227 hasConcept C111919701 @default.
- W3173239227 hasConcept C136764020 @default.
- W3173239227 hasConcept C199360897 @default.
- W3173239227 hasConcept C2522767166 @default.
- W3173239227 hasConcept C41008148 @default.
- W3173239227 hasConcept C48044578 @default.
- W3173239227 hasConcept C519991488 @default.
- W3173239227 hasConcept C77088390 @default.
- W3173239227 hasConcept C79974875 @default.
- W3173239227 hasConceptScore W3173239227C111919701 @default.
- W3173239227 hasConceptScore W3173239227C136764020 @default.
- W3173239227 hasConceptScore W3173239227C199360897 @default.
- W3173239227 hasConceptScore W3173239227C2522767166 @default.
- W3173239227 hasConceptScore W3173239227C41008148 @default.
- W3173239227 hasConceptScore W3173239227C48044578 @default.
- W3173239227 hasConceptScore W3173239227C519991488 @default.
- W3173239227 hasConceptScore W3173239227C77088390 @default.
- W3173239227 hasConceptScore W3173239227C79974875 @default.
- W3173239227 hasLocation W31732392271 @default.
- W3173239227 hasOpenAccess W3173239227 @default.
- W3173239227 hasPrimaryLocation W31732392271 @default.
- W3173239227 hasRelatedWork W2460999112 @default.
- W3173239227 hasRelatedWork W2761048258 @default.
- W3173239227 hasRelatedWork W2803657496 @default.
- W3173239227 hasRelatedWork W2890741686 @default.
- W3173239227 hasRelatedWork W2898761039 @default.
- W3173239227 hasRelatedWork W2921710879 @default.
- W3173239227 hasRelatedWork W2948984390 @default.
- W3173239227 hasRelatedWork W2976735527 @default.
- W3173239227 hasRelatedWork W2980625652 @default.
- W3173239227 hasRelatedWork W3001235209 @default.
- W3173239227 hasRelatedWork W3035622004 @default.
- W3173239227 hasRelatedWork W3035650989 @default.
- W3173239227 hasRelatedWork W3113236902 @default.
- W3173239227 hasRelatedWork W3161591992 @default.
- W3173239227 hasRelatedWork W3162149541 @default.
- W3173239227 hasRelatedWork W3165702510 @default.
- W3173239227 hasRelatedWork W3183492702 @default.
- W3173239227 hasRelatedWork W3187031798 @default.
- W3173239227 hasRelatedWork W3193321391 @default.
- W3173239227 hasRelatedWork W3193566184 @default.
- W3173239227 isParatext "false" @default.
- W3173239227 isRetracted "false" @default.
- W3173239227 magId "3173239227" @default.
- W3173239227 workType "book" @default.