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The Machine Learning Solutions Architect Handbook
Author David Ping
Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutionsKey FeaturesExplore different ML tools and frameworks to solve large-scale machine learning challenges in the cloudBuild an efficient data science environment for data explorat....
Release Date 2022/01 -
Machine Learning Engineering with MLflow
Get up and running, and productive in no time with MLflow using the most effective machine learning engineering approachKey FeaturesExplore machine learning workflows for stating ML problems in a concise and clear manner using MLflowUse MLflow to iteratively develop a ML model and manage it Discover.... -
Data Science Projects with Python - Second Edition
Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoostKey FeaturesThink critically about data and use it to form and test a hypothesisChoose an appropriate machine learning model and train it on your dataCommunicate d.... -
Applied Regression Modeling, 3rd Edition
Master the fundamentals of regression without learning calculus with this one-stop resourceThe newly and thoroughly revised 3rd Edition of Applied Regression Modeling delivers a concise but comprehensive treatment of the application of statistical regression analysis for those with little or no back.... -
Supervised Learning with Python: Concepts and Practical Implementation Using Python
Author Vaibhav Verdhan
Gain a thorough understanding of supervised learning algorithms by developing use cases with Python. You will study supervised learning concepts, Python code, datasets, best practices, resolution of common issues and pitfalls, and practical knowledge of implementing algor....
Release Date 2020/10 -
The Data Science Workshop - Second Edition
Author Anthony So , Thomas V. Joseph , Robert Thas John
Gain expert guidance on how to successfully develop machine learning models in Python and build your own unique data platformsKey FeaturesGain a full understanding of the model production and deployment processBuild your first machine learning model in just five minutes a....
Release Date 2020/08 -
The Machine Learning Workshop - Second Edition
Author Hyatt Saleh
Take a comprehensive and step-by-step approach to understanding machine learningKey FeaturesDiscover how to apply the scikit-learn uniform API in all types of machine learning models Understand the difference between supervised and unsupervised learning models Reinforce....
Release Date 2020/07 -
Hands-on Scikit-Learn for Machine Learning Applications: Data Science Fundamentals with Python
Author David Paper
Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised....
Release Date 2019/11 -
Machine Learning with scikit-learn Quick Start Guide
Author Kevin Jolly
Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering.Key FeaturesBuild your first machine learning model using scikit-learn Train supervised and unsupervised models using popular tec....
Release Date 2018/10 -
Author Olga Korotkova
Random Light Beams: Theory and Applications contemplates the potential in harnessing random light. This book discusses light matter interactions, and concentrates on the various phenomena associated with beam-like fields. It explores natural and man-made light field....
Release Date 2017/12 -
scikit-learn Cookbook - Second Edition
Author Julian Avila
Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications.About This BookHandle a variety of machine learning tasks effortlessly by leveraging the power of scikit-learnPerform supervised and unsupervised learning with ea....
Release Date 2017/11 -
scikit-learn : Machine Learning Simplified
Author Gavin Hackeling , Trent Hauck , Guillermo Moncecchi , Raúl Garreta
Implement scikit-learn into every step of the data science pipelineAbout This BookUse Python and scikit-learn to create intelligent applicationsDiscover how to apply algorithms in a variety of situations to tackle common and not-so common challenges in the machine ....
Release Date 2017/11 -
Mastering Machine Learning with scikit-learn - Second Edition
Author Gavin Hackeling
Use scikit-learn to apply machine learning to real-world problemsAbout This BookMaster popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networksLearn how to build and eva....
Release Date 2017/07 -
Python: Real World Machine Learning
Author Alberto Boschetti , Luca Massaron , Bastiaan Sjardin , John Hearty , Prateek Joshi
Learn to solve challenging data science problems by building powerful machine learning models using PythonAbout This BookUnderstand which algorithms to use in a given context with the help of this exciting recipe-based guideThis practical tutorial tackles real-world....
Release Date 2016/11 -
Mastering Machine Learning with scikit-learn
Author Gavin Hackeling
Apply effective learning algorithms to real-world problems using scikit-learnIn DetailThis book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing docu....
Release Date 2014/10 -
Learning scikit-learn: Machine Learning in Python
Author Guillermo Moncecchi , Raúl Garreta
Incorporating machine learning in your applications is becoming essential. As a programmer this book is the ideal introduction to scikit-learn for your Python environment, taking your skills to a whole new level.Use Python and scikit-learn to create intelligent appl....
Release Date 2013/11 -
Author Michael I. Brown
It is now well accepted that deforestation is a key source of greenhouse gas emissions and of climate change, with forests representing major sinks for carbon. As a result, public and private initiatives for reducing emissions from deforestation and forest degradati....
Release Date 2013/06 -
Applied Logistic Regression, 3rd Edition
Author Rodney X. Sturdivant , Stanley Lemeshow , David W. Hosmer , Jr.
A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this mo....
Release Date 2013/04