9781484286913 - modern deep learning for tabular data: novel approaches to common modeling problems de ye, andre; wang, zian (35 resultados)
- Tapa blanda
Librería: Books From California, Simi Valley, CA, Estados Unidos de AmericaBooks From California
Contactar con el vendedorVendedor de 4 estrellasCondición: Usado - Bueno
EUR 32,74
Envío por EUR 4,35Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
paperback. Condición: Very Good.
- Tapa blanda
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 37,45
Envío por EUR 2,30Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
- Más imágenes
- Tapa blanda
Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 39,83
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular dat…a. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data.Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage.Modern Deep Learning for Tabular Data is one of the first of its kind - a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems.What You Will LearnImportant concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications.Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isn't appropriate.Apply promising research and unique modeling approaches in real-world data contexts.Explore and engage with modern, research-backed theoretical advances on deep tabular modelingUtilize unique and successful preprocessing methods to prepare tabular data for successful modelling.Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security.
- Tapa blanda
Librería: Lakeside Books, Benton Harbor, MI, Estados Unidos de AmericaLakeside Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 37,19
Envío por EUR 3,48Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.
- Más imágenes
- Tapa blanda
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de AmericaBargainBookStores
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 43,68
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 5 disponibles
Paperback or Softback. Condición: New. Modern Deep Learning for Tabular Data: Novel Approaches to Common Modeling Problems. Book.
- Tapa blanda
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 44,91
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
- Más imágenes
- Tapa blanda
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 43,51
Envío por EUR 2,30Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
- Tapa blanda
Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 40,76
Envío por EUR 14,97Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback / softback. Condición: New. New copy - Usually dispatched within 2 working days.
- Tapa blanda
Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 50,23
Envío por EUR 11,00Se envía de Italia a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Condición: new.
- Tapa blanda
- Edición internacional
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de AmericaRomtrade Corp.
Contactar con el vendedorVendedor de 5 estrellasEdición internacionalCondición: Nuevo
EUR 64,02
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be print…ed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
- Más imágenes
- Tapa blanda
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 46,94
Envío por EUR 17,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
- Tapa blanda
Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 54,08
Envío por EUR 13,96Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. In.
- Tapa blanda
Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 50,78
Envío por EUR 18,06Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 10 disponibles
PF. Condición: New.
- Tapa blanda
- Primera edición
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 69,96
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain ta…bular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data an incredibly ubiquitous form of structured data.Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks through both their default usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage.Modern Deep Learning for Tabular Data is one of the first of its kind a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems.What You Will LearnImportant concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications.Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isnt appropriate.Apply promising research and unique modeling approaches in real-world data contexts.Explore and engage with modern, research-backed theoretical advances on deep tabular modelingUtilize unique and successful preprocessing methods to prepare tabular data for successful modelling.Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Tapa blanda
- Primera edición
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 59,53
Envío por EUR 9,50Se envía de Irlanda a Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: New. 2022. 1st ed. paperback. . . . . .
- Tapa blanda
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 53,96
Envío por EUR 17,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
- Tapa blanda
Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,91
Envío por EUR 18,06Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
paperback. Condición: New.
- Tapa blanda
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 74,36
Envío por EUR 9,16Se envía dentro de Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: New. 2022. 1st ed. paperback. . . . . . Books ship from the US and Ireland.
- Tapa blanda
Librería: Brook Bookstore, Milano, MI, ItaliaBrook Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 45,49
Envío por EUR 37,99Se envía de Italia a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Condición: new.
- Tapa blanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 72,02
Envío por EUR 17,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 870 pages. 10.00x7.01x1.73 inches. In Stock.
- Tapa blanda
Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 92,49
Envío por EUR 3,48Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. 1st ed. edition NO-PA16APR2015-KAP.
- Más imágenes
- Tapa blanda
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 40,75
Envío por EUR 75,77Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular dat…a. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data.Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage.Modern Deep Learning for Tabular Data is one of the first of its kind - a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems.What You Will LearnImportant concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications.Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isn't appropriate.Apply promising research and unique modeling approaches in real-world data contexts.Explore and engage with modern, research-backed theoretical advances on deep tabular modelingUtilize unique and successful preprocessing methods to prepare tabular data for successful modelling.Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security.
- Más imágenes
- Tapa blanda
Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 59,40
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Taschenbuch. Condición: Neu. Modern Deep Learning for Tabular Data | Novel Approaches to Common Modeling Problems | Andre Ye (u. a.) | Taschenbuch | xxviii | Englisch | 2022 | Apress | EAN 9781484286913 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[d…ot]hartmann[at]springer[dot]com | Anbieter: preigu.
- Tapa blanda
- Primera edición
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 108,77
Envío por EUR 32,27Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain ta…bular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data an incredibly ubiquitous form of structured data.Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks through both their default usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage.Modern Deep Learning for Tabular Data is one of the first of its kind a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems.What You Will LearnImportant concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications.Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isnt appropriate.Apply promising research and unique modeling approaches in real-world data contexts.Explore and engage with modern, research-backed theoretical advances on deep tabular modelingUtilize unique and successful preprocessing methods to prepare tabular data for successful modelling.Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Tapa blanda
Librería: Buchpark, Trebbin, AlemaniaBuchpark
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Bueno
EUR 43,53
Envío por EUR 105,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Gut. Zustand: Gut | Seiten: 872 | Sprache: Englisch | Produktart: Bücher | Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learn…ing approaches to a seemingly unlikely domain ¿ tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data ¿ an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs ¿ Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks ¿ through both their ¿default¿ usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage. Modern Deep Learning for Tabular Data is one of the first of its kind ¿ a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems. What You Will Learn Important concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications. Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isn¿t appropriate. Apply promising research and unique modeling approaches in real-world data contexts. Explore and engage with modern, research-backed theoretical advances on deep tabular modeling Utilize unique and successful preprocessing methods to prepare tabular data for successful modelling. Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security.
- Tapa blanda
Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, AlemaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Bueno
EUR 179,95
Envío por EUR 39,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Softcover. Condición: gut. 2022. Modern Deep Learning for Tabular Data In englischer Sprache. pages.
- Tapa blanda
- Impresión bajo demanda
Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 46,95
Envío por EUR 18,36Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Tapa blanda
- Impresión bajo demanda
Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 69,10
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 10 disponibles
Condición: Brand New. New. Delivery takes 20-25 days. Print on Demand.
- Tapa blanda
- Impresión bajo demanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 66,02
Envío por EUR 17,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 870 pages. 10.00x7.01x1.73 inches. In Stock. This item is printed on demand.
- Más imágenes
- Tapa blanda
- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 64,19
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents nove…l deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data.Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage.Modern Deep Learning for Tabular Data is one of the first of its kind - a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems.What You Will LearnImportant concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications.Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isn't appropriate.Apply promising research and unique modeling approaches in real-world data contexts.Explore and engage with modern, research-backed theoretical advances on deep tabular modelingUtilize unique and successful preprocessing methods to prepare tabular data for successful modelling.Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security. 872 pp. Englisch.
