Verwandte Artikel zu Bayesian Methods for Hackers: Probabilistic Programming...

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics) (Addison-Wesley Data and Analytics) - Softcover

 
9780133902839: Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics) (Addison-Wesley Data and Analytics)

Inhaltsangabe

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power.

Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention.

Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects.

Coverage includes

• Learning the Bayesian “state of mind” and its practical implications

• Understanding how computers perform Bayesian inference

• Using the PyMC Python library to program Bayesian analyses

• Building and debugging models with PyMC

• Testing your model’s “goodness of fit”

• Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works

• Leveraging the power of the “Law of Large Numbers”

• Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning

• Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes

• Selecting appropriate priors and understanding how their influence changes with dataset size

• Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough

• Using Bayesian inference to improve A/B testing

• Solving data science problems when only small amounts of data are available

Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Cameron Davidson-Pilon has seen many fields of applied mathematics, from evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His main contributions to the open-source community include Bayesian Methods for Hackers and lifelines. Cameron was raised in Guelph, Ontario, but was educated at the University of Waterloo and Independent University of Moscow. He currently lives in Ottawa, Ontario, working with the online commerce leader Shopify.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Gebraucht kaufen

Zustand: Sehr gut
Diesen Artikel anzeigen

EUR 1,99 für den Versand von Tschechien nach Deutschland

Versandziele, Kosten & Dauer

EUR 2,32 für den Versand von Vereinigtes Königreich nach Deutschland

Versandziele, Kosten & Dauer

Weitere beliebte Ausgaben desselben Titels

9789353063641: Bayesian Methods For Hackers: Probabilistic Programming And Bayesian Inference

Vorgestellte Ausgabe

ISBN 10:  9353063647 ISBN 13:  9789353063641
Softcover

Suchergebnisse für Bayesian Methods for Hackers: Probabilistic Programming...

Foto des Verkäufers

Cameron Davidson-Pilon
Verlag: Pearson Education (US), 2015
ISBN 10: 0133902838 ISBN 13: 9780133902839
Gebraucht Softcover

Anbieter: Bookbot, Prague, Tschechien

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Softcover. Zustand: Fine. Bestandsnummer des Verkäufers 20e9e04f-dae2-4a48-a0ee-0ae95a0fa4f3

Verkäufer kontaktieren

Gebraucht kaufen

EUR 21,49
Währung umrechnen
Versand: EUR 1,99
Von Tschechien nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Davidson-Pilon, Cameron Davidson-Pilon
ISBN 10: 0133902838 ISBN 13: 9780133902839
Gebraucht Paperback

Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Bestandsnummer des Verkäufers GOR009876050

Verkäufer kontaktieren

Gebraucht kaufen

EUR 24,85
Währung umrechnen
Versand: EUR 4,06
Von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Foto des Verkäufers

Cameron Davidson-Pilon
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Paperback

Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich

Verkäuferbewertung 4 von 5 Sternen 4 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Paperback. Zustand: New. Master Bayesian Inference through Practical Examples and Computation-Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes . Learning the Bayesian "state of mind" and its practical implications . Understanding how computers perform Bayesian inference . Using the PyMC Python library to program Bayesian analyses . Building and debugging models with PyMC . Testing your model's "goodness of fit" . Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works . Leveraging the power of the "Law of Large Numbers" . Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning . Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes . Selecting appropriate priors and understanding how their influence changes with dataset size . Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough . Using Bayesian inference to improve A/B testing . Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify. Bestandsnummer des Verkäufers LU-9780133902839

Verkäufer kontaktieren

Neu kaufen

EUR 29,23
Währung umrechnen
Versand: EUR 2,32
Von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Foto des Verkäufers

Cameron Davidson-Pilon
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Paperback

Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes Königreich

Verkäuferbewertung 4 von 5 Sternen 4 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Paperback. Zustand: New. Master Bayesian Inference through Practical Examples and Computation-Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes . Learning the Bayesian "state of mind" and its practical implications . Understanding how computers perform Bayesian inference . Using the PyMC Python library to program Bayesian analyses . Building and debugging models with PyMC . Testing your model's "goodness of fit" . Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works . Leveraging the power of the "Law of Large Numbers" . Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning . Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes . Selecting appropriate priors and understanding how their influence changes with dataset size . Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough . Using Bayesian inference to improve A/B testing . Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify. Bestandsnummer des Verkäufers LU-9780133902839

Verkäufer kontaktieren

Neu kaufen

EUR 33,08
Währung umrechnen
Versand: EUR 2,32
Von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Foto des Verkäufers

Cameron Davidson-Pilon
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Taschenbuch

Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Taschenbuch. Zustand: Neu. Neuware - The next generation of problems will not have deterministic solutions - the solutions will be statistical that rely on mountains, or mounds, of data. Bayesian methods offer a very flexible and extendible framework to solve these types of problems. For programming students with minimal background in mathematics, this example-heavy guide emphasizes the new technologies that have allowed the inference to be abstracted from complicated underlying mathematics. Using Bayesian Methods for Hackers, students can start leveraging powerful Bayesian tools right now -- gradually deepening their theoretical knowledge while already achieving powerful results in areas ranging from marketing to finance. Bestandsnummer des Verkäufers 9780133902839

Verkäufer kontaktieren

Neu kaufen

EUR 40,51
Währung umrechnen
Versand: Gratis
Innerhalb Deutschlands
Versandziele, Kosten & Dauer

Anzahl: 2 verfügbar

In den Warenkorb

Foto des Verkäufers

Davidson-Pilon, Cameron
Verlag: Addison-Wesley, 2015
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Softcover

Anbieter: moluna, Greven, Deutschland

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. The next generation of problems will not have deterministic solutions - the solutions will be statistical that rely on mountains, or mounds, of data. Bayesian methods offer a very flexible and extendible framework to solve these types of problems. For progr. Bestandsnummer des Verkäufers 32947812

Verkäufer kontaktieren

Neu kaufen

EUR 41,61
Währung umrechnen
Versand: Gratis
Innerhalb Deutschlands
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Cameron Davidson-Pilon
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Softcover Erstausgabe

Anbieter: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irland

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. . 2015. 1st Edition. Paperback. . . . . Bestandsnummer des Verkäufers V9780133902839

Verkäufer kontaktieren

Neu kaufen

EUR 43,80
Währung umrechnen
Versand: EUR 2,00
Von Irland nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Foto des Verkäufers

Davidson-pilon, Cameron
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Softcover

Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. Bestandsnummer des Verkäufers 21512063-n

Verkäufer kontaktieren

Neu kaufen

EUR 29,21
Währung umrechnen
Versand: EUR 17,42
Von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Beispielbild für diese ISBN

Davidson-Pilon, Cameron Davidson-Pilon
ISBN 10: 0133902838 ISBN 13: 9780133902839
Gebraucht Softcover

Anbieter: SecondSale, Montgomery, IL, USA

Verkäuferbewertung 4 von 5 Sternen 4 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Bestandsnummer des Verkäufers 00089485339

Verkäufer kontaktieren

Gebraucht kaufen

EUR 17,99
Währung umrechnen
Versand: EUR 29,73
Von USA nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 1 verfügbar

In den Warenkorb

Foto des Verkäufers

Davidson-pilon, Cameron
ISBN 10: 0133902838 ISBN 13: 9780133902839
Neu Softcover

Anbieter: GreatBookPrices, Columbia, MD, USA

Verkäuferbewertung 5 von 5 Sternen 5 Sterne, Erfahren Sie mehr über Verkäufer-Bewertungen

Zustand: New. Bestandsnummer des Verkäufers 21512063-n

Verkäufer kontaktieren

Neu kaufen

EUR 30,76
Währung umrechnen
Versand: EUR 16,98
Von USA nach Deutschland
Versandziele, Kosten & Dauer

Anzahl: 3 verfügbar

In den Warenkorb

Es gibt 8 weitere Exemplare dieses Buches

Alle Suchergebnisse ansehen