Computer Software中的新品排行榜

#1

Data Engineering Excellence: Architecting Resilient Systems from Scratch to Scale (The Innovators of AI and Data Series Book 3)

Kai W. Calder

Kindle电子书

#2

Data Science in 30 Days: The Complete Beginner’s Guide (Zero to Hero in 30 Days: The Accelerated Learning Series)

Kindle电子书

#3

Robert Osazuwa Ness

Kindle电子书

#4

The Curious Case of ChatterBotGPT: A Bold New Perspective On Generative AI in Business

Kindle电子书

#5

The Art of Prompt Engineering for ChatGPT : Master GPT-4, DALL E,ADA and Plugins for Practical Success (The Art of AI Prompting)

Kindle电子书

#6

Python for Data Analysis: A Beginner's Guide to Data Science (Data Decoded: The Beginner's Journey)

Kindle电子书

#7

AI for Beginners Made Simple: The Easy Guide to Quickly Learn About Artificial Intelligence and How Smart Tech will Shape the Future So You can Scale Faster with Automation

Kindle电子书

#8

Unpacking DeepSeek R1: A Developers Guide to Building AI Agents That Reason (The Complete AI Blueprint Book 4)

James Karanja Maina

Kindle电子书

#9

Reshuffle: Who wins when AI restacks the knowledge economy

Sangeet Paul Choudary

Kindle电子书

#10

Microsoft Office 365 Non-Tech Savvy Bible: [10 in 1]: From Beginner to Pro with This Fully Illustrated Guide– Word, Excel, PowerPoint, Access, Outlook, Skype, Teams, OneDrive, OneNote, and Publisher

Alan Norwood

Kindle电子书

#11

Microsoft Excel 365 Data Analysis Masterclass: A Practical Guide to Power Query, Power Pivot, DAX, and Data Visualization (The Microsoft 365 Mastery Series)

LIAM P. SWIFT

Kindle电子书

#12

Leaders Make the Future, Third Edition: Ten New Skills to Humanize Leadership with Generative AI

Kindle电子书

#13

Microsoft Teams Bible: Step-by-Step Guide to Effective Team Collaboration, From Permissions to Encryption, Auditing Features, and Troubleshooting Common ... Project Management (Microsoft Office)

Kindle电子书

#14

AI Agents in Action

Kindle电子书

#15

MASTERING QUICKEN : The Comprehensive Guide to Personal and Business Finance: Track, Budget, and Grow Your Wealth with Ease

JAMES K. LEDGER

Kindle电子书

#16

AI For Grannies: A Friendly Guide to AI for the Elderly (And Not So...) (A 10 Book Series 1)

Sergio Prizont

Kindle电子书

#17

Machine Learning System Design: With end-to-end examples

Valerii Babuskhin

Kindle电子书

#18

DeepSeek AI for Entrepreneurs: Automate, Innovate , and Outperform

Nova Callahan

Kindle电子书

#19

The Art of Prompt Engineering for Code Generation : Master AI-Powered Coding with GitHub Copilot, OpenAI Codex, and ChatGPT (The Art of AI Prompting)

Kindle电子书

#20

A First Course in Statistical Learning: With Data Examples and Python Code (Statistics and Computing)

Johannes Lederer

Kindle电子书

#21

Python Polars: The Definitive Guide: Transforming, Analyzing, and Visualizing Data with a Fast and Expressive DataFrame API

Jeroen Janssens

Kindle电子书

#22

Monday.com for Project Managers: Blueprint to Success: Streamlining Workflow and Team Collaboration with Monday.com

R. Parvin

Kindle电子书

#23

Databricks Certified Data Engineer Associate Study Guide

Derar Alhussein

Kindle电子书

#24

Considerations on the AI Endgame: Ethics, Risks and Computational Frameworks (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

Soenke Ziesche

Kindle电子书

#25

Agentic AI with RAG in Action: Enhance AI Agents, AI Prompt Engineering, Generative AI and AI Edge Sales Strategies systems using Agentic RAG

Kindle电子书

#26

The Well-Grounded Data Analyst: Solve messy data problems like a pro

Kindle电子书

#27

AI-Powered Search

Kindle电子书

#28

Getting to Know Mobile GIS

Kindle电子书

#29

Mastering Agentic AI: Building Autonomous AI Agents with LLMs, Reinforcement Learning, and Multi-Agent Systems

Kindle电子书

#30

Graph RAG for AI: The Essential Blueprint for Smarter Retrieval, Reasoning & Knowledge Graphs (The AI Architect’s Guide: Graph-Based Retrieval, AI Agents, and Advanced Generative AI)

Kindle电子书

AI Guide for Beginners: How to Use AI Prompts & Master Artificial Intelligence in 4 Practical Days (21 Days To Make Money Wit

AI Engineering: Building Applications with Foundation Models

Build a Large Language Model (From Scratch)

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