Python编程无师自通

python机器学习教程-从零开始掌握Python机器学习：十四步教程.pdf

python机器学习教程_从零开始掌握Python机器学习：⼗四步 教程 Python 可以说是现在最流⾏的机器学习语⾔，⽽且你也能在⽹上找到⼤量的资源。你现在也在考虑从 Python ⼊门机器学习吗？本教程或 许能帮你成功上⼿，从 0 到 1 掌握 Python 机器学习，⾄于后⾯再从 1 到 100 变成机器学习专家，就要看你⾃⼰的努⼒了。本教程原⽂ 分为两个部分，机器之⼼在本⽂中将其进⾏了整合，原⽂可参阅：7 Steps to Mastering Machine Learning With Python 和 7 More Steps to Mastering Machine Learning With Python。本教程的作者为 KDnuggets 副主编兼数据科学家 Matthew Mayo。 「开始」往往是最难的，尤其是当选择太多的时候，⼀个⼈往往很难下定决定做出选择。本教程的⽬的是帮助⼏乎没有 Python 机器学习背 景的新⼿成长为知识渊博的实践者，⽽且这个过程中仅需要使⽤免费的材料和资源即可。这个⼤纲的主要⽬标是带你了解那些数量繁多的可 ⽤资源。毫⽆疑问，资源确实有很

机器学习的数学基础 machine learning.pdf

机器学习的数学基础 machine learning.pdf

Python Machine Learning.pdf 无水印书签修正完美版 2015

原pdf书签没有链接正确，本人对此进行了修正 Paperback: 454 pages Publisher: Packt Publishing - ebooks Account (September 2015) Language: English ISBN-10: 1783555130 ISBN-13: 978-1783555130 Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask and answer tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data

Python Machine Learning 2nd Edition [Sebastian Raschka]

What you will learn Understand the key frameworks in data science, machine learning, and deep learning Harness the power of the latest Python open source libraries in machine learning Explore machine learning techniques using challenging real-world data Master deep neural network implementation using the TensorFlow library Learn the mechanics of classification algorithms to implement the best tool for the job Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Delve deeper into textual and social media data using sentiment analysis

python machine learning 最新版 2nd second edition

python machine learning 最新版 2nd second edition

python1.使用while循环实现输出2-3+4-5+6...+100 的和_一个倔强的女孩的博客-CSDN博客_python1+2+3+4+5+6+…+100代码.pdf

python1.使用while循环实现输出2-3+4-5+6...+100 的和_一个倔强的女孩的博客-CSDN博客_python1+2+3+4+5+6+…+100代码.pdf

python_docx-0.8.10-py2.py3-none-any.whl

估计这个安装包还只兼容python 2(python2 和python3差别还是挺大的，虽然现在python 3出来很久了，但是不少三方库还没有更新)，因此需要自己找一个兼容的包：python_docx-0.8.6-py2.py3-none-any.whl。然后在...

Python库 | certifi-2021.5.30-py2.py3-none-any.whl

资源分类：Python库 所属语言：Python 资源全名：certifi-2021.5.30-py2.py3-none-any.whl 资源来源：官方 安装方法：https://lanzao.blog.csdn.net/article/details/101784059

OpenCV-Python-Toturial-中文版.pdf

OpenCV-Python-Toturial-中文版.pdf

Python Machine Learning

About This Book, Leverage Python' s most powerful open-source libraries for deep learning, data wrangling, and data visualization, Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms, Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets, Who This Book Is For, If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource., What You Will Learn, Explore how to use different machine learning models to ask different questions of your data, Learn how to build neural networks using Keras and Theano, Find out how to write clean and elegant Python code that will optimize the strength of your algorithms, Discover how to embed your machine learning model in a web application for increased accessibility, Predict continuous target outcomes using regression analysis, Uncover hidden patterns and structures in data with clustering, Organize data using effective pre-processing techniques, Get to grips with sentiment analysis to delve deeper into textual and social media data, Style and approach, Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Learning Python中文版

Python语言入门-----Learning Python中文版

Python.Machine.Learning

Python Machine Learning 2019 Wiley Chapter 1 Introduction to Machine Learning 1 Chapter 2 Extending Python Using NumPy 19 Chapter 3 Manipulating Tabular Data Using Pandas 39 Chapter 4 Data Visualization Using matplotlib 67 Chapter 5 Getting Started with Scikit-learn for Machine Learning 93 Chapter 6 Supervised Learning—Linear Regression 119 Chapter 7 Supervised Learning—Classifcation Using Logistic Regression 151 Chapter 8 Supervised Learning—Classifcation Using Support Vector Machines 177 Chapter 9 Supervised Learning—Classifcation Using K-Nearest Neighbors (KNN) 205 Chapter 10 Unsupervised Learning—Clustering Using K-Means 221 Chapter 11 Using Azure Machine Learning Studio 243 Chapter 12 Deploying Machine Learning Models 269

MachineLearning-master-python.zip

属于网络下载资源，感谢原作者的贡献。 ##目录介绍 - **DeepLearning Tutorials** 这个文件夹下包含一些深度学习算法的实现代码，以及具体的应用实例，包含： Keras使用进阶。介绍了怎么保存训练好的CNN模型，怎么将CNN用作特征提取，怎么可视化卷积图。 [keras_usage]介绍了一个简单易用的深度学习框架keras，用经典的Mnist分类问题对该框架的使用进行说明，训练一个CNN，总共不超过30行代码。 将卷积神经网络CNN应用于人脸识别的一个demo，人脸数据库采用olivettifaces，CNN模型参考LeNet5，基于python+theano+numpy+PIL实现。 CNN卷积神经网络算法的实现，模型为简化版的LeNet，应用于MNIST数据集（手写数字），来自于DeepLearning.net上的一个教程，基于python+theano 多层感知机算法的实现，代码实现了最简单的三层感知机，并应用于MNIST数据集。 [Softmax_sgd(or logistic_sgd)]Softmax回归算法的实现，应用于MNIST数据集，基于Python+theano。 - **PCA** 基于python+numpy实现了主成份分析PCA算法 - **kNN** 基于python+numpy实现了K近邻算法，并将其应用在MNIST数据集上， - **logistic regression** - 基于C++以及线性代数库Eigen实现的logistic回归，[代码] - 基于python+numpy实现了logistic回归（二类别） - **ManifoldLearning** 运用多种流形学习方法将高维数据降维，并用matplotlib将数据可视化(2维和3维) - **SVM** - **GMM** GMM和k-means作为EM算法的应用，在某种程度有些相似之处，不过GMM明显学习出一些概率密度函数来，结合相关理解写成python版本 - **DecisionTree** Python、Numpy、Matplotlib实现的ID3、C4.5，其中C4.5有待完善，后续加入CART。 - **KMeans** 介绍了聚类分析中最常用的KMeans算法（及二分KMeans算法），基于NumPy的算法实现，以及基于Matplotlib的聚类过程可视化。 朴素贝叶斯算法的理论推导，以及三种常见模型（多项式模型，高斯模型，伯努利模型）的介绍与编程实现（基于Python，Numpy）

Python Machine Learning - Second Edition

Python Machine Learning - Second Edition -Second edition of the bestselling book on Machine Learning

Python+MySQL-python-1.2.3.win32-py2.7.msi+setuptools-0.6c11.win32-py2.7.exe

包含Python MySQL-python-1.2.3.win32-py2.7.msi setuptools-0.6c11.win32-py2.7.exe chromedriver_win_23.0.1240.0.zip IEDriverServer_Win32_2.25.3.zip

Python Machine Learning.PDF文档+代码

Python Machine Learning(First Edition-第1版）PDF文档以及相应代码

opencv-python 3.4.1.15 opencv-contrib-python 3.4.1.15 win64版

opencv-python 3.4.1.15 opencv-contrib-python 3.4.1.15 win64版，opencv-python 3.4.1.15 opencv-contrib-python 3.4.1.15，支持版本：python3.4，3.5，3.6

Hands-on-data-science-and-Python-machine-learning-perform-data-mining-and-machine-learning-efficiently-using-Python-and- ....pdf

Hands-on-data-science-and-Python-machine-learning-perform-data-mining-and-machine-learning-efficiently-using-Python-and-Spark.pdf

Python Machine Learning, 2nd Edition-Packt Publishing(2017).pdf )

addition to offering a hands-on experience with machine learning using the Python programming languages and Python-based machine learning libraries, this book introduces the mathematical concepts ...

python machine learning 2nd pdf

python machine learning 2nd pdf python machine learning 2nd pdf

Python Machine Learning.pdf

Machine learning is transforming the way businesses operate. Being able to understand trends and patterns in complex data is critical to success; it is today one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your d

Machine Learning by Tutorials (2nd Edition).pdf

Covers CoreML, Vison, image and sequence classifiers, natural language processing, and more. Get started with Machine Learning for Apple and iOS! Want to know a secret? Machine learning isn’t really that hard to learn. The truth is, you don’t need a PhD from a prestigious university or a background in mathematics to do machine learning. If you already know how to code, you can pick up machine learning quite easily — promise! This book will get you started with machine learning on iOS and Apple devices. The first bit is a gentle introduction to the world of machine learning and what it has to offer — as well as what its limitations are. In the rest of the book, you’ll look at each of these topics in more detail, until you know enough to make machine learning a useful tool in your software development toolbox. There are now several high-level Apple frameworks, including Natural Language, Speech, and Vision, that provide advanced machine learning functionality behind simple APIs as part of Apple’s iOS tooling. Whether you want to convert speech to text, recognize language or grammatical structure, detect faces in photos or track moving objects in video, these frameworks have got you covered. In this book, you’ll learn how to use these tools and frameworks to make your apps smarter. Even better, you’ll learn how machine learning works behind the scenes — and why this technology is awesome. This book is for all Apple and iOS developers who are interested in learning how to train models, code image recognition systems, learn how natural language processing works, build sequence classifiers and more.

Real-World Machine Learning 无水印pdf

Real-World Machine Learning 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

Machine Learning Algorithms 无水印pdf

Machine Learning Algorithms 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

Python数据可视化实战 教案全 第1-8章.docx.pdf

Python数据可视化实战 教案全 第1-8章.docx.pdfPython数据可视化实战 教案全 第1-8章.docx.pdfPython数据可视化实战 教案全 第1-8章.docx.pdfPython数据可视化实战 教案全 第1-8章.docx.pdfPython数据可视化实战 ...

Python编程基础(视频讲解版)-教学大纲.pdf

Python编程基础(视频讲解版)-教学大纲.pdfPython编程基础(视频讲解版)-教学大纲.pdfPython编程基础(视频讲解版)-教学大纲.pdfPython编程基础(视频讲解版)-教学大纲.pdfPython编程基础(视频讲解版)-教学大纲.pdf...

Designing-Machine-Learning-Systems-with-Python.pdf.pdf

Designing-Machine-Learning-Systems-with-Python.pdf

Learn+Python+3+the+Hard+Way-Addison-Wesley(2017).pdf

This book instructs you in Python by slowly building and establishing skills through techniques such as practice and memorization, then applying them to increasingly di cult problems. By the end of ...

OpenCV-Python-Toturial-中文版.pdf&用Python做科学计算.pdf

OpenCV-Python-Toturial-中文版.pdf&用Python做科学计算.pdf