Bayesian Analysis with Python : A practical guide to probabilistic modeling

Bayesian Analysis with Python : A practical guide to probabilistic modeling

Αποθηκεύτηκε σε:

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας:	Martin, Osvaldo A. (19..-). (Συγγραφέας)
Άλλοι συγγραφείς:	Fonnesbeck, Christopher. (Préface), Wiecki, Thomas.
Μορφή:	E-Book
Γλώσσα:	Anglais
Έκδοση:	Birmingham : Packt Publishing.
Autres localisations:	Voir dans le Sudoc
Διαθέσιμο Online:	Accès à l'E-book

Παρόμοια τεκμήρια

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Advancements in Bayesian Methods and Implementations
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Time Series Analysis with Python Cookbook : Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation
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Enhancing Deep Learning with Bayesian Inference : Create more powerful, robust deep learning systems with Bayesian deep learning in Python
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Regression analysis with Python
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Python Data Analysis : Perform data collection, data processing, wrangling, visualization, and model building using Python
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Hands-on Markov models with Python : implement probabilistic models for learning complex data sequences using the Python ecosystem
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Big Data Analysis with Python : Combine Spark and Python to unlock the powers of parallel computing and machine learning
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Mastering geospatial analysis with Python : explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter
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Hands-On Exploratory Data Analysis with Python : Perform EDA techniques to understand, summarize, and investigate your data
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Graph Data Modeling in Python : A practical guide to curating, analyzing, and modeling data with graphs
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Exploratory Data Analysis with Python Cookbook : Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
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Machine Learning for Emotion Analysis in Python : Build AI-powered tools for analyzing emotion using natural language processing and machine learning
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The Design Analysis Handbook A Practical Guide to Design Validation
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Power Systems Modelling and Fault Analysis : Theory and Practice
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