Revealed Sciences
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Revealed Sciences
Author | : Justin K. Stearns |
Publsiher | : Cambridge University Press |
Total Pages | : 331 |
Release | : 2021-07-08 |
Genre | : History |
ISBN | : 9781107065574 |
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Provides a detailed overview of the place of the natural sciences in the scholarly and educational landscape of Early Modern Morocco, this study challenges previous negative depictions of the natural sciences in the Muslim world to demonstrate the vibrancy of an Early Modern Muslim society in seventeenth-century Morocco.
The Presbyterian Review
Author | : Charles Augustus Briggs,Archibald Alexander Hodge,Francis Landrey Patton,Benjamin Breckenridge Warfield |
Publsiher | : Unknown |
Total Pages | : 816 |
Release | : 1885 |
Genre | : Presbyterian Church |
ISBN | : WISC:89077096964 |
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Includes section "Reviews of recent theological literature".
Appletons Popular Science Monthly
Author | : William Jay Youmans |
Publsiher | : Unknown |
Total Pages | : 1130 |
Release | : 1898 |
Genre | : Science |
ISBN | : HARVARD:TZ1AED |
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The Science of Belief
![The Science of Belief](https://youbookinc.com/wp-content/themes/mts_schema/cover.jpg)
Author | : Bradley Stubbs |
Publsiher | : Unknown |
Total Pages | : 110 |
Release | : 2017-11-05 |
Genre | : Electronic Book |
ISBN | : 1549742515 |
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The greatest book to create the greatest winning mindset. A unique book that gives anyone the edge over their opposition in terms of mindset and their ability to win. Bradley Charles Stubbs, the Coach Whisperer takes you on a journey through the mind. While he makes you aware of your strengths he empowers your weaknesses to ensure winning results. The Science of Belief is an extension on Neuroscience. Whilst neuroscience understands the brain, the science of belief puts the brain into action. It develops techniques to activate the brain into a winning mindset.
The Popular Science Monthly
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 798 |
Release | : 1873 |
Genre | : Science |
ISBN | : MINN:31951T00080716K |
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Century Illustrated Monthly Magazine
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 982 |
Release | : 1893 |
Genre | : Periodicals |
ISBN | : CHI:72981649 |
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Scribner s Monthly an Illustrated Magazine for the People
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 962 |
Release | : 1893 |
Genre | : Electronic Book |
ISBN | : PSU:000020213619 |
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Data Science Revealed
Author | : Tshepo Chris Nokeri |
Publsiher | : Apress |
Total Pages | : 252 |
Release | : 2021-03-21 |
Genre | : Computers |
ISBN | : 1484268695 |
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Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models. Each chapter includes a set of examples allowing you to understand the concepts, assumptions, and procedures behind each model. The book covers parametric methods or linear models that combat under- or over-fitting using techniques such as Lasso and Ridge. It includes complex regression analysis with time series smoothing, decomposition, and forecasting. It takes a fresh look at non-parametric models for binary classification (logistic regression analysis) and ensemble methods such as decision trees, support vector machines, and naive Bayes. It covers the most popular non-parametric method for time-event data (the Kaplan-Meier estimator). It also covers ways of solving classification problems using artificial neural networks such as restricted Boltzmann machines, multi-layer perceptrons, and deep belief networks. The book discusses unsupervised learning clustering techniques such as the K-means method, agglomerative and Dbscan approaches, and dimension reduction techniques such as Feature Importance, Principal Component Analysis, and Linear Discriminant Analysis. And it introduces driverless artificial intelligence using H2O. After reading this book, you will be able to develop, test, validate, and optimize statistical machine learning and deep learning models, and engineer, visualize, and interpret sets of data. What You Will Learn Design, develop, train, and validate machine learning and deep learning models Find optimal hyper parameters for superior model performance Improve model performance using techniques such as dimension reduction and regularization Extract meaningful insights for decision making using data visualization Who This Book Is For Beginning and intermediate level data scientists and machine learning engineers