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Hands-On Data Science and Python Machine Learning

Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python’s Matplotlib library Use Apache Spark’s MLlib package to perform machine learning on large datasets
2018-04-15 上传大小:15.28MB
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Hands-On Data Science and Python Machine Learning py

Hands-On Data Science and Python Machine Learning py

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Hands-On Machine Learning with Scikit-Learn and TensorFlow [EPUB]

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron English | 2017 | ISBN: 1491962291 | 566 Pages | EPUB | 8.41 MB Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details

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Hands-On.Machine.Learning.with.Scikit-Learn.and.TensorFlow含代码

Hands-On.Machine.Learning.with.Scikit-Learn.and.TensorFlow,原书及代码,今年新书,797页 A sequence of data processing components is called a data pipeline. Pipelines are very common in Machine Learning systems, since there is a lot of data to manipulate and many data transformations to apply. Components typically run asynchronously. Each component pulls in a large amount of data, processes it, and spits out the result in another data store, and then some time later the next component in the pipeline pulls this data and spits out its own output, and so on. Each component is fairly self-contained: the interface between components is simply the data store. This makes the system quite simple to grasp (with the help of a data flow graph), and different teams can focus on different components. Moreover, if a component breaks down, the downstream components can often continue to run normally (at least for a while) by just using the last output from the broken component. This makes the architecture quite robust. On the other hand, a broken component can go unnoticed for some time if proper monitoring is not implemented. The data gets stale and the overall system’s performance drops.

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Hands-On Machine Learning with Scikit-Learn and TensorFlow+无码高清扫描+文字可复制+完整标签

本书是Aurélien Géron 2017年推出的新书,流行于各大深度学习网站,本书无码高清扫描,附带完整标签,文字代码示例均可复制编辑,并可长期归档PDF/A,堪称完美,非常适合想学习Tensorflow和SL库的朋友!强烈推荐!

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《Hands-On Machine Learning with Scikit-Learn and TensorFlow》代码

下载地址:https://github.com/ageron/handson-ml 图书介绍: Hands-On Machine Learning with Scikit-Learn and TensorFlow Concepts, Tools, and Techniques for Building Intelligent Systems By Aurélien Géron Publisher: O'Reilly Media Release Date: July 2016 Pages: 581 A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you. This hands-on book shows you how to use: Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry point TensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networks Practical code examples that you can apply without learning excessive machine learning theory or algorithm details

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Hands-On Machine Learning with Scikit-Learn and TensorFlow 完整版共797页 非扫描版 人工智能 机器学习经典书籍

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Hands-On Machine Learning with Scikit-Learn and TensorFlow(中文翻译版),是一本很好的工具书,可以帮助你更好的理解sklearn 和TensorFlow在机器学习中的应用

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【高清】+【英文原版】+【PDF格式】Hands-On Machine Learning with Scikit-Learn and TensorFlow

高清、英文原版,美国亚马逊排名第一的tensorflow学习指导书籍,销量最好,评价五星!

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Hands-On Machine Learning with Scikit-Learn and TensorFlow(pdf 带标签+github代码)

Hands-On Machine Learning with Scikit-Learn and TensorFlow(pdf 带标签+github代码)

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Hands-On Machine Learning with Scikit-Learn and TensorFlow Concepts...

Hands-On Machine Learning with Scikit-Learn and TensorFlow Concepts, Tools, and Techniques to Build Intelligent System 英文高清版pdf 随书代码下载地址: https://github.com/ageron/handson-ml

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Hands-On Data Science and Python Machine Learning azw3

Hands-On Data Science and Python Machine Learning 英文azw3 本资源转载自网络,如有侵权,请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

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Hands-On Data Science and Python Machine Learning epub

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.Hands-On.Machine.Learning.with.Scikit-Learn.and.TensorFlow-google翻译中文版

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Hands On Machine Learning with Scikit-Learn and TensorFlow超清PDF,中文版+英文版

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Hands-On Data Science with Anaconda

Hands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools on the market to perform data science operations. It's also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications using the best libraries in multiple languages. Basic programming knowledge with R or Python and basic knowledge of linear algebra is expected.

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