McConnaughy, Tim

McNutt, Steve

Miles, Christopher

A pragmatic guide to acing the AWS ANS-C01 exam

AWS Certified Advanced Networking – Specialty (ANS-C01) Certification Guide

Malavasi, Alexandre

A project-based guide to building web applications with ASP.NET Core 9 and JavaScript frameworks

Modern Full-Stack Web Development with ASP.NET Core

Despoudis, Theofanis

Build clean and scalable apps with proven patterns and expert insights

TypeScript 5 Design Patterns and Best Practices

Verma, Jatin

Build a solid foundation in Snowflake to pass the SnowPro Core exam on the first attempt

SnowPro Core Certification Study Guide

Mukherjee, Amit

Casalaina, Marco

Saladi, Adithya

A practical guide to unlocking generative AI-powered innovation with Azure OpenAI

Azure OpenAI Essentials

Loredo, Robert

Write your own practical quantum programs with Python

Learn Quantum Computing with Python and IBM Quantum

Najlaa, Najihah

Master video editing with expert tips, techniques, and workflows

The Complete Guide to Adobe Premiere Pro 2025

Makhija, Jagjeet Singh

Odunukwe, Charles

Boost your skills with expert insights and certification-ready strategies for Microsoft analytics

Implementing Analytics Solutions Using Microsoft Fabric—DP-600 Exam Study Guide

Belmansour, Tidjani

Brady, Damian

A step-by-step guide to developing cross-platform CLI apps—from coding and testing to deployment

Building CLI Applications with C# and .NET

Apperson, Lem

Weinberger, Jonathan

Leverage C# scripting in Unity to create immersive games and VR experiences

Unity 6 Game Development with C# Scripting

Chinese Edition

Python机器学习案例精解

<span xml:lang="zh">Python机器学习案例精解: Chinese Edition</span>

Press, Posts & Telecom

Liu, Yuxi (Hayden)

用简单易学的示例，带你驶入机器学习的快车道Key Features书中示例浅显易懂，涵盖多种应用场景讲解方式生动有趣。Book Description本书开篇介绍Python语言和机器学习开发环境的搭建方法。后续章节介绍相关的重要概念，比如数据分析、数据预处理、特征抽取、数据可视化、聚类、分类、回归和模型性能度量等。本书包含多个项目案例，涉及几种重要且有趣的机器学习算法，引导读者从头实现自己的模型。学完本书，你将了解机器学习生态系统的全貌，并掌握机器学习技术的实践和应用。 在本书的帮助下，你将学会用强大却很简单的Python语言来处理数据科学难题，并构建自己的解决方案。书中示例浅显易懂，涵盖多种应用场景：新闻话题分类、垃圾邮件过滤、在线广告点击率预测和股票价格预测等，讲解方式生动有趣。 • 本书包括以下内容： • 利用Python语言抽取数据、处理数据和探索数据； • 用Python对多维数据进行可视化，并抽取有用特征； • 深入钻研数据分析技术，正确预测发展趋势； • 用Python从头实现机器学习分类算法和回归算法； • 用雅虎财经数据来分析和预测股价； • 评估并优化机器学习模型的性能； • 用机器学习和Python解决实际问题。What you will...

用简单易学的示例，带你驶入机器学习的快车道Key Features书中示例浅显易懂，涵盖多种应用场景讲解方式生动有趣。Book...

Format

Python机器学习案例精解

Chinese Edition

Posts & Telecom Press

Yuxi (Hayden) Liu

People Also Read