Personnaliser

OK

Informations importantes : Arrêt du Club R (13 août) et Cessation d'Activité (30 septembre)

En savoir plus.

Rakuten - Achat et vente en ligne de produits neufs et d'occasionRakuten group
ClubR
Person

Se connecter

Heart
Cart
Rakuten - Achat et vente en ligne de produits neufs et d'occasionRakuten group
ClubR
Person

Se connecter

Cart
Rentrée
Rentrée
Cartes cadeaux
Cartes cadeaux
Smartphones et Tablettes
Smartphones et Tablettes
Électroménager
Électroménager
Livres
Livres
Livraison 48h
Livraison 48h
Econometrics And Data Science de Nokeri, Tshepo Chris Format Broché

Econometrics and Data Science - Nokeri, Tshepo Chris

Note : 0

0 avis
  • Soyez le premier à donner un avis

38,23 €

Produit Neuf

  • Ou 9,56 € /mois

    • En savoir plus
    • Livraison : 3,99 €
    • Livré entre le 24 septembre et le 1 octobre
    Voir les modes de livraison

    M_plus_L

    PRO Vendeur favori

    4,8/5 sur + de 1 000 ventes

    Voir le détail de l'annonce
    Publicité
     
    Vous avez choisi le retrait chez le vendeur à
    • Payez directement sur Rakuten (CB, PayPal, 4xCB...)
    • Récupérez le produit directement chez le vendeur
    • Rakuten vous rembourse en cas de problème
    Terminer ma commande

    Gratuit et sans engagement

    Félicitations !

    Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !

    En savoir plus

    TROUVER UN MAGASIN

      Retour

      Horaires

          Note :


          Avis sur Econometrics And Data Science de Nokeri, Tshepo Chris Format Broché  - Livre Économie

          Note : 0 0 avis sur Econometrics And Data Science de Nokeri, Tshepo Chris Format Broché  - Livre Économie

          Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.


          Présentation Econometrics And Data Science de Nokeri, Tshepo Chris Format Broché

           - Livre Économie

          Livre Économie - Nokeri, Tshepo Chris - 30/09/2021 - Broché - Langue : Anglais

          . .

        • Auteur(s) : Nokeri, Tshepo Chris
        • Editeur : Apress
        • Langue : Anglais
        • Parution : 30/09/2021
        • Format : Moyen, de 350g à 1kg
        • Nombre de pages : 248
        • Expédition : 474
        • Dimensions : 25.4 x 17.8 x 1.4
        • ISBN : 9781484274330



          • Résumé :
          Get up to speed on the application of machine learning approaches in macroeconomic research. This book brings together economics and data science.

          Author Tshepo Chris Nokeri begins by introducing you to covariance analysis, correlation analysis, cross-validation, hyperparameter optimization, regression analysis, and residual analysis. In addition, he presents an approach to contend with multi-collinearity. He then debunks a time series model recognized as the additive model. He reveals a technique for binarizing an economic feature to perform classification analysis using logistic regression. He brings in the Hidden Markov Model, used to discover hidden patterns and growth in the world economy. The author demonstrates unsupervised machine learning techniques such as principal component analysis and cluster analysis. Key deep learning concepts and ways of structuring artificial neural networks are explored along with training them and assessing their performance. The Monte Carlo simulation technique is applied to stimulate the purchasing power of money in an economy. Lastly, the Structural Equation Model (SEM) is considered to integrate correlation analysis, factor analysis, multivariate analysis, causal analysis, and path analysis.
          After reading this book, you should be able to recognize the connection between econometrics and data science. You will know how to apply a machine learning approach to modeling complex economic problems and others beyond this book. You will know how to circumvent and enhance model performance, together with the practical implications of a machine learning approach in econometrics, and you will be able to deal with pressing economic problems.
          What You Will Learn
          Examine complex, multivariate, linear-causal structures through the path and structural analysis technique, including non-linearity and hidden states Be familiar with practical applications of machine learning and deep learning in econometrics Understand theoretical framework and hypothesis development, and techniques for selecting appropriate models Develop, test, validate, and improve key supervised (i.e., regression and classification) and unsupervised (i.e., dimension reduction and cluster analysis) machine learning models, alongside neural networks, Markov, and SEM models Represent and interpret data and models
          Who This Book Is For
          Beginning and intermediate data scientists, economists, machine learning engineers, statisticians, and business executives
          ...

          Biographie:
          Tshepo Chris Nokeri harnesses big data, advanced analytics, and artificial intelligence to foster innovation and optimize business performance. In his functional work, he has delivered complex solutions to companies in the mining, petroleum, and manufacturing industries. He initially completed a bachelor's degree in information management. He then graduated with an honors degree in business science at the University of the Witwatersrand on a TATA Prestigious Scholarship and a Wits Postgraduate Merit Award. He was unanimously awarded the Oxford University Press Prize. He has authored two Apress books: Data Science Revealed: With Feature Engineering, Data Visualization, Pipeline Development, and Hyperparameter Tuning, and Implementing Machine Learning for Finance: A Systematic Approach to Predictive Risk and Performance Analysis for Investment Portfolios....

          Sommaire:
          Get up to speed on the application of machine learning approaches in macroeconomic research. This book brings together economics and data science.

          Author Tshepo Chris Nokeri begins by introducing you to covariance analysis, correlation analysis, cross-validation, hyperparameter optimization, regression analysis, and residual analysis. In addition, he presents an approach to contend with multi-collinearity. He then debunks a time series model recognized as the additive model. He reveals a technique for binarizing an economic feature to perform classification analysis using logistic regression. He brings in the Hidden Markov Model, used to discover hidden patterns and growth in the world economy. The author demonstrates unsupervised machine learning techniques such as principal component analysis and cluster analysis. Key deep learning concepts and ways of structuring artificial neural networks are explored along with training them and assessing their performance. The Monte Carlo simulation technique is applied to stimulate the purchasing power of money in an economy. Lastly, the Structural Equation Model (SEM) is considered to integrate correlation analysis, factor analysis, multivariate analysis, causal analysis, and path analysis.
          After reading this book, you should be able to recognize the connection between econometrics and data science. You will know how to apply a machine learning approach to modeling complex economic problems and others beyond this book. You will know how to circumvent and enhance model performance, together with the practical implications of a machine learning approach in econometrics, and you will be able to deal with pressing economic problems.
          What You Will Learn
          Examine complex, multivariate, linear-causal structures through the path and structural analysis technique, including non-linearity and hidden states Be familiar with practical applications of machine learning and deep learning in econometrics Understand theoretical framework and hypothesis development, and techniques for selecting appropriate models Develop, test, validate, and improve key supervised (i.e., regression and classification) and unsupervised (i.e., dimension reduction and cluster analysis) machine learning models, alongside neural networks, Markov, and SEM models Represent and interpret data and models
          Who This Book Is For
          Beginning and intermediate data scientists, economists, machine learning engineers, statisticians, and business executives
          ...

          Détails de conformité du produit

          Consulter les détails de conformité de ce produit (

          Personne responsable dans l'UE

          )
          Le choixNeuf et occasion
          Le service clientsÀ votre écoute
          • Liens utiles
            • Mon compte
            • Mon panier
            • Paiement en plusieurs fois
            • Vendre
            • Suivre ma commande
            • Mon Club R
          • Aide
            • Besoin d'aide ?
            • Ouvrir un e-shop en tant que commerçant
            • Frais de protection acheteurs
            • Signaler un contenu illicite
            • Plan du site
            • Le blog
          • Rakuten
            • Carrières
            • Conditions générales
            • *Conditions des offres
            • Politique Vie privée
            • Gestion des cookies
            • Affiliation
            • Devenez annonceur
            • A propos de Rakuten
            • Fonctionnement du service
            • Assurances
          LinkedinFacebookTwitterInstagramYoutubePinterestTiktok
          visavisa
          mastercardmastercard
          klarnaklarna
          paypalpaypal
          floafloa
          americanexpressamericanexpress
          Application AppstoreApplication Android
          Rakuten Logo
          • Rakuten Kobo
          • Rakuten TV
          • Rakuten Viber
          • Rakuten Viki
          • Plus de services
          • À propos de Rakuten
          Rakuten.com

          © Rakuten France 2000 - 2026