应用as3.0进行游戏开发的高级教程，带源码，有各种算法的详细讲解

进阶LabVIEW编程，适合对LabVIEW编程有较高要求的人使用

房屋价格-高级_回归_技术

Digital Signal Processing and Noise Reduction 4th Edition

视频设计软件用于视频剪辑

图 7.17 被分割后的两个 7．2．6 对盘面划分网 本小节中将选用 PLANE42 单元对盘面划分映射网格。 （1）单击 Main Menu | Preprocessor | Meshing | MeshTool，弹出 Mesh Tool（网格工具）， 如图 7.18 所示。 Generated by Foxit PDF Creator © Foxit Software http://www.foxitsoftware.com For evaluation only.

视频加密一机一码，图片加密U盘加密软件，软件加密软件，压缩包加密软件

使用动态蒙版对象进行溶解：球体、箱体、圆柱体、圆锥体、平面、每轴 (X,Y,Z)

Python: Advanced Predictive Analytics: Gain practical insights by exploiting data in your business to build advanced predictive modeling applications Python: Advanced Predictive Analytics: Gain practical insights by exploiting data in your business to build advanced predictive modeling applications By 作者: Ashish Kumar – Joseph Babcock ISBN-10 书号: 1788992369 ISBN-13 书号: 9781788992367 Release 出版日期: 2017-12-27 pages 页数: (660 ) $99.99 Python: Advanced Predictive Analytics: Gain practical insights by exploiting data in your business to build advanced predictive modeling applications Gain practical insights by exploiting data in your business to build advanced predictive modeling applications Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You’ll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling. Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books: Learning Predictive Analytics with Python Mastering Predictive Analytics with Python What You Will Learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis