Numerical Recipes in C
C语言数值算法大全 经典作品
2021-10-29 12:03:42
7.37MB
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Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis.
Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing.
By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient.
What You Will Learn
Apply NLP techniques using Python libraries such as NLTK, TextBlob, spaCy, Stanford CoreNLP, and many more
Implement the concepts of information retrieval, text summarization, sentiment analysis, and other advanced natural language processing techniques.
Identify machine learning and deep learning techniques for natural language processing and natural language generation problems
Who This Book Is For
Data scientists who want to refresh and learn various concepts of natural language processing through coding exercises.
2021-10-21 23:45:54
3.84MB
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决策树分类matlab代码应用机器学习和数据科学食谱-面向初学者的数据科学编码训练营
使用Python，R和MATLAB的应用机器学习和数据科学
适用于应用机器学习和数据科学的Python，R和MATLAB代码列表
应用机器学习和数据科学的7个步骤：
通过编码分类学习：
分类：
数据分析：
数据科学：
数据可视化：
机器学习食谱：
熊猫：
Python：
SKLEARN：
监督学习：
表格数据分析：
端到端数据科学食谱：
应用统计：
套袋乐团：
促进合奏：
CatBoost：
聚类：
数据分析：
数据科学：
数据可视化：
决策树：
LightGBM：
机器学习食谱：
多类别分类：
神经网络：
Python机器学习：
Python机器学习速成课程：
R分类：
R对于初学者：
R
for
Business
Analytics：
R
for
Data
Science：
用于数据可视化的R：
适用于Excel用户的R：
R机器学习：
R机器学习速成课程：
R回归：
回归：
XGBOOST：
有抱负的数据科学家的项目组合项目：表格文本和图像数据分析以及Python和R
@中的时间序列预测
西澳大
2021-10-19 16:49:27
1KB
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Numerical Recipes - The Art of Scientific Computing(3rd)【数值分析方法库pdf】无水印
[数值分析方法库].Cambridge.Press.Numerical.Recipes.3rd.Edition
Numerical Recipes - The Art of Scientific Computing(3rd) 无水印pdf
Numerical Recipes - The Art of Scientific Computing(3rd) 英文无水印pdf 第3版
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
2021-10-13 22:04:20
7.52MB
用于烹饪食谱检索的深度学习食物图像识别系统
演示：DeepChef
总览
更新：博客文章现已发布。 有关更多信息，请访问！
例如用法，请访问此Jupyter Notebook：
Maturaarbeit 2018：这项工作利用Keras的深度卷积神经网络将图像分类为230种食物并输出匹配的食谱。 数据集包含来自chefkoch.de的> 400'000食物图像和> 300'000食谱。
几乎没有任何其他领域能像营养一样对人类福祉产生类似的影响。 每天，用户都会在社交网络上发布无数的食物图片； 从第一个自制蛋糕到顶级米其林菜肴，万一菜肴成功，您将与世界分享快乐。 事实是，无论彼此之间有多大差异，美食都会受到大家的赞赏。 个别烹饪原料的分类或对象识别方面的进展很少。 问题在于几乎没有公开编辑的记录。
处理
该代码（Jupyter笔记本）提供了许多德语注释。 该过程如下所示：
1│──数据准备│└──清除数据│└──数据扩充
2│──数据分析和可视化，拆分数据（训练，有效，测试）
3│──使用简单ML模型的首次尝试│└──最近邻分类器（kNN） │└──k-均值聚类│└──支持向量机
2021-09-20 12:35:20
199.37MB
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中文版 有书签 C++ 数值算法 第二版 第一部分
作者：William H. Press等，出版社：Cambridge University Press.是集各种数值计算方法之大全，除C++版外，还有 C 语言版，Fortran77 和Fortran90版，此外还有PASCAL语言版，BASCIC语言版，并且有与其配套的各语言的程序。
好不容易把书签给弄好了，有需要的请下载。
2021-09-13 14:37:56
10MB
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中文版 有书签 C++ 数值算法 第二版 第二部分
作者：William H. Press等，出版社：Cambridge University Press.是集各种数值计算方法之大全，除C++版外，还有 C 语言版，Fortran77 和Fortran90版，此外还有PASCAL语言版，BASCIC语言版，并且有与其配套的各语言的程序。
好不容易把书签给弄好了，有需要的请下载。
2021-09-13 14:15:53
6.07MB
1
数值计算（c/c++）的好书：
Review
'The author's engaging writing style makes this a very enjoyable book. Each topic starts with interesting observational material, then goes to a discussion of the physical concepts, amplified by mathematics, and very good figures, and then ties it up by finishing with more observational applications, either solving the problem posed at the beginning of the chapter or presenting new ones. This is a perfect book for seniors.' - Marc L. Kutner, author of Astronomy: A Physical Perspective
'A lucid introduction to a selection of basic topics in astronomy, explaining the physics behind the astrophysics. Radiative processes are treated with just the right level of rigor that students learn how to carry out useful computations while developing their physical intuition. I have successfully used portions of this book for my first-year graduate class.' - Eugene Chiang, Associate Professor of Astronomy, University of California, Berkeley
Review of Astronomy Methods, also by Hale Bradt: '... a brilliant addition to the pedagogy. It is timely, focused, well written, and at the appropriate level ... Astronomy Methods will be useful to all students of astronomy and astrophysics, irrespective of whether they intend to specialize in observational astronomy. The material can be adapted easily for various related courses, which makes the book even more valuable.' - Physics Today
2021-08-10 19:48:46
7.57MB
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涵盖数值分析大多数算法，含C++代码
2021-08-03 09:20:36
9.6MB
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