Search Results - (( machines library. ) OR ( machine library. ))

Machines / by DeLeon, Abraham P.

Table of Contents: “…Cover; Series; Machines; Library of Congress Cataloging-in-Publication Data; Contents; Preface; Acknowledgements; Chapter 1: Locating the Machines; Chapter 2: Capitalism and Its Machines; Chapter 3: Colonial Machines; Chapter 4: Post-Machines ... …”
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Machine Learning Paradigms Artificial Immune Systems and their Applications in Software Personalization / by Sotiropoulos, Dionisios N., Tsihrintzis, George A.

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Machine Learning Paradigms Advances in Data Analytics /

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Designing Machine Learning Systems. by Huyen, Chip

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Reverse Hypothesis Machine Learning A Practitioner's Perspective / by Kulkarni, Parag

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Interpretable Machine Learning with Python : Build Explainable, Fair, and Robust High-Performance Models with Hands-on, Real-world Examples. by Mas�is, Serg

Table of Contents: “…-- A business case for interpretability -- Better decisions -- More trusted brands -- More ethical -- More profitable -- Summary -- Image sources -- Dataset sources -- Further reading -- Chapter 2: Key Concepts of Interpretability -- Technical requirements -- The mission -- Details about CVD -- The approach -- Preparations -- Loading the libraries -- Understanding and preparing the data -- The data dictionary -- Data preparation -- Interpretation method types and scopes -- Model interpretability method types -- Model interpretability scopes -- Interpreting individual predictions with logistic regression -- Appreciating what hinders machine learning interpretability -- Non-linearity -- Interactivity -- Non-monotonicity -- Mission accomplished -- Summary -- Further reading -- Chapter 3: Interpretation Challenges -- Technical requirements -- The mission -- The approach -- The preparations -- Loading the libraries -- Understanding and preparing the data -- The data dictionary -- Data preparation -- Reviewing traditional model interpretation methods -- Predicting minutes delayed with various regression methods -- Classifying flights as delayed or not delayed with various classification methods -- Training and evaluating the classification models.…”
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Machine Learning for Evolution Strategies by Kramer, Oliver

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Interpretable Machine Learning with Python : Build Explainable, Fair, and Robust High-Performance Models with Hands-on, Real-world Examples / by Masis, Serg, Molak, Aleksander, Rothman, Denis

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From Curve Fitting to Machine Learning An Illustrative Guide to Scientific Data Analysis and Computational Intelligence / by Zielesny, Achim

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Visual Knowledge Discovery and Machine Learning by Kovalerchuk, Boris

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Machine Learning Algorithms for Signal and Image Processing. by Ghai, Deepika

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Python for Probability, Statistics, and Machine Learning by Unpingco, José

Table of Contents: “…Introduction -- Part 1 Getting Started with Scientific Python -- Installation and Setup -- Numpy -- Matplotlib -- Ipython -- Jupyter Notebook -- Scipy -- Pandas -- Sympy -- Interfacing with Compiled Libraries -- Integrated Development Environments -- Quick Guide to Performance and Parallel Programming -- Other Resources -- Part 2 Probability -- Introduction -- Projection Methods -- Conditional Expectation as Projection -- Conditional Expectation and Mean Squared Error -- Worked Examples of Conditional Expectation and Mean Square Error Optimization -- Useful Distributions -- Information Entropy -- Moment Generating Functions -- Monte Carlo Sampling Methods -- Useful Inequalities -- Part 3 Statistics -- Python Modules for Statistics -- Types of Convergence -- Estimation Using Maximum Likelihood -- Hypothesis Testing and P-Values -- Confidence Intervals -- Linear Regression -- Maximum A-Posteriori -- Robust Statistics -- Bootstrapping -- Gauss Markov -- Nonparametric Methods -- Survival Analysis -- Part 4 Machine Learning -- Introduction -- Python Machine Learning Modules -- Theory of Learning -- Decision Trees -- Boosting Trees -- Logistic Regression -- Generalized Linear Models -- Regularization -- Support Vector Machines -- Dimensionality Reduction -- Clustering -- Ensemble Methods -- Deep Learning -- Notation -- References -- Index.…”
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Feature engineering bookcamp / by Ozdemir, Sinan

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Feature Engineering Bookcamp. by Ozdemir, Sinan

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Deep learning with Python / by Chollet, Francois

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Deep Learning with Python, Second Edition. by Chollet, Francois

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Machine learning algorithms for signal and image processing /

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Deep Learning : Foundations and Concepts / by Bishop, Christopher M., Bishop, Hugh

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Deep Learning : Foundations and Concepts. by Bishop, Christopher M.

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Time-Series Prediction and Applications A Machine Intelligence Approach / by Konar, Amit, Bhattacharya, Diptendu

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