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deep learning coders fastai di howard jeremy (32 risultati)
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Paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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Aggiungi al carrelloSoftcover. Condizione: Fair. Wasserschaden / Verschmutzung; Gebogener Buchrücken; Deutlicher Riss. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work.
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
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Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD (Paperback or Softback)
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Paperback or Softback. Condizione: New. Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD. Book.
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Deep Learning for Coders with Fastai and Pytorch
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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Deep Learning for Coders with fastai and PyTorch
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
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Aggiungi al carrelloPaperback. Condizione: New. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala.
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
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Paperback. Condizione: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
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Deep Learning for Coders With Fastai and Pytorch : AI Applications Without a Phd
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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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Deep Learning for Coders with fastai and PyTorch
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Aggiungi al carrelloPaperback. Condizione: New. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala.
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Deep Learning for Coders with fastai and PyTorch
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Deep Learning for Coders With Fastai and Pytorch: Ai Applications Without a Phd
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Aggiungi al carrellopaperback. Condizione: Gut. 621 Seiten; 9781492045526.3 Gewicht in Gramm: 2.
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Deep Learning for Coders with fastai and PyTorch
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Deep Learning for Coders with fastai and PyTorch
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Paperback. Condizione: New. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Deep Learning for Coders with Fastai and Pytorch | AI Applications Without a PhD | Jeremy Howard (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | O'Reilly Media | EAN 9781492045526 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Deep Learning for Coders with fastai and PyTorch
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Aggiungi al carrelloPaperback. Condizione: New. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala.
