@kirkdborne

–

16 October 2026 6h28

Supervised Learning and Unsupervised Learning infographic ————
#DataScience #ML #MachineLearning

16 October 2026

LLM Customization Resource Covers Adaptation, Distillation and Alignment

By

–

16 October 2026 6h22

Upcoming release from @ManningBooks — you can preorder this book now with the *very beneficial* Amazon price guarantee. "LLM Customization and Fine-Tuning: Adaptation, distillation, and alignment" Check it out: https://
link.amazon/B03h5U2Gl Publisher's comment: "For ML engineers,

16 October 2026

Data Without Labels Teaches Practical Unsupervised Machine Learning

By

–

16 October 2026 6h17

Data Without Labels — Models and Algorithms for Practical Unsupervised Machine Learning: https://
amzn.to/4q5bbYz 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷: 🔶Fundamental building blocks and concepts of machine learning and unsupervised learning
🔶Data cleaning for structured and

16 October 2026

Agent Engineering Resource Covers Routing, Collaboration, Memory and Retrieval

By

–

15 October 2026 20h50

https://
link.amazon/B03fWztIo 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
♦️Apply foundational principles to design production-ready agents
♦️Design agent communication, routing, and collaboration flows
♦️Orchestrate teams with proven multi-agent design patterns
♦️Manage memory, retrieval,

Guide Builds Agentic AI Applications With C Sharp and .NET

By

–

15 October 2026 20h46

Agentic AI Development with C# and .NET — Build intelligent Applications with GitHub Copilot, Microsoft Agent Framework, and Azure AI Foundry: https://
link.amazon/B0dfKwfN5 v/ @PacktPublishing 𝙏𝙖𝙗𝙡𝙚 𝙊𝙛 𝘾𝙤𝙣𝙩𝙚𝙣𝙩𝙨:
♦️Intro to AI-Augmented Development in .NET 10
♦️Set Up

Textbook Applies Linear Algebra and Optimization to Machine Learning

By

–

15 October 2026 17h31

Linear Algebra and Optimization for Machine Learning [516-page textbook]: https://
amzn.to/39aWf8N
—
This textbook is organized around its 2 main themes: [Amazon Summary] 1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with

Scikit Learn Cookbook Covers Preprocessing and Dimensionality Reduction

By

–

15 October 2026 17h27

💥Scikit-learn Cookbook — 80+ recipes for Machine Learning in Python with scikit-learn [3rd Edition]: https://
amzn.to/4oDGOq7 𝓒𝓸𝓷𝓽𝓮𝓷𝓽𝓼:
🔹Common Conventions & API Elements of Scikit-Learn
🔹Pre-Model Workflow and Data Preprocessing
🔹Dimensionality Reduction Techniques

Python Guide Applies Machine Learning to Financial Risk Management

By

–

15 October 2026 17h26

Machine Learning for Financial Risk Management with Python — Algorithms for Modeling Risk: https://
amzn.to/3t7ARbG
—————
#AI #DataScience #DataScientist #ML #Finance #Fintech #Insurtech #PredictiveAnalytics

Finance Textbook Explores Quantum Machine Learning and Optimization

By

–

15 October 2026 17h25

CFO, CEO, financial analyst, tech entrepreneur, student, job-seeker, friends & family — be future-ready with this book >> "Quantum Machine Learning and Optimization in Finance" (494 pages; 2nd Edition): https://
link.amazon/B00GpBIKy