| 書目名稱 | Mastering Machine Learning with Python in Six Steps | | 副標(biāo)題 | A Practical Implemen | | 編輯 | Manohar Swamynathan | | 視頻video | http://file.papertrans.cn/626/625478/625478.mp4 | | 概述 | Compares different machine learning framework implementations for each topic.Covers Reinforcement Learning and Convolutional Neural Networks.Explains best practices for model tuning for better model a | | 圖書封面 |  | | 描述 | .Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner.?This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable?Python 3 packages..You’ll start with the fundamentals of?Python 3?programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as exploratory analysis, feature dimension reduction, regressions, time series forecasting and their efficient implementation in Scikit-learn are covered as well. You’ll also learn commonly used model diagnostic and tuning techniques. These include optimal probability cutoff point for class creation, variance, bias, bagging, boosting, ensemble voting, grid search, random search,?Bayesian optimization, and?the noise reduction technique for IoT data.?. .Finally, you’ll review advanced text mining techniques, recommender systems, neural networks, deep learning, reinforcement learning techniques and their implementation. | | 出版日期 | Book 2019Latest edition | | 關(guān)鍵詞 | Machine Learning; Python; Scikit-Learn; Model Tuning; Text Mining; Neural Networks; Deep Learning; Recommen | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4842-4947-5 | | isbn_softcover | 978-1-4842-4946-8 | | isbn_ebook | 978-1-4842-4947-5 | | copyright | Manohar Swamynathan 2019 |
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