Python Pour La Data Science
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Python en pratique pour le data scientist
Python s'est imposé ces dernières années comme un langage de programmation incontournable dans de nombreux domaines. En science des données (data science), il se distingue comme un outil essentiel pour mener à bien des projets complexes grâce à son caractère universel. Il constitue aujourd'hui l'outil de choix pour la création de prototypes et un allié incontournable dans les domaines du big data, du machine learning, du deep learning et de l'intelligence artificielle. Cet ouvrage a pour but de vous accompagner dans la découverte de Python, un langage à la fois simple d'utilisation et puissant pour les utilisateurs travaillant avec les données. L'objectif est de vous fournir les connaissances nécessaires pour comprendre et maitriser Python dans le contexte de la data science. Pour quiconque aspire à devenir data scientist ou l'est déjà, la maitrise de Python est désormais un impératif.
Hands-On Data Science with Anaconda
Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda Key Features -Use Anaconda to find solutions for clustering, classification, and linear regression -Analyze your data efficiently with the most powerful data science stack -Use the Anaconda cloud to store, share, and discover projects and libraries Book Description Anaconda 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. What you will learn Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda Use the package manager conda and discover, install, and use functionally efficient and scalable packages Get comfortable with heterogeneous data exploration using multiple languages within a project Perform distributed computing and use Anaconda Accelerate to optimize computational powers Discover and share packages, notebooks, and environments, and use shared project drives on Anaconda Cloud Tackle advanced data prediction problems Who this book is for Hands-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.