AI Engineering — Building Applications with Foundation Models: http://
amzn.to/4aiSv1O by @chipro —
#ML #MachineLearning #DataScience #DataScientist
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𝓣𝓸𝓹𝓲𝓬𝓼:
Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the
RESEARCH
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AI Engineering: Building Applications with Foundation Models
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Concrete Mathematics: Essential Foundation for Computer Science
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Concrete [CONtinuous and disCRETE] Mathematics — A Foundation for Computer Science (and for serious users of mathematics in virtually every discipline): http://
amzn.to/4oGfeJn [672 pages] Topics covered: Evaluating Horrendous Sums Recurrences Integer functions -
Introduction to Probability, Statistics, and Random Processes
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Introduction to Probability, Statistics, and Random Processes: http://
amzn.to/3UkLHXZ
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#DataScience #Mathematics #DataScientist -
Understanding Uncertainty: Probability and Statistics Fundamentals
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What are the Chances of That? How to Think About Uncertainty: http://
amzn.to/4q7atJi by @itabn_andrew #Probability #Statistics #Mathematics -
Mathematics of Machine Learning Book Review and Guide
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Get "Mathematics of Machine Learning" here: http://
amzn.to/4eN7i52 by @TivadarDanka v/ @PacktDataML —
GitHub: http://
github.com/cosmic-cortex/
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Here is my review: 𝗧𝗵𝗲 𝗦𝗲𝘁 𝗢𝗳 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 𝗧𝗵𝗮𝘁 𝗟𝗲𝗮𝗿𝗻 𝗙𝗿𝗼𝗺 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 This -
Context Engineering for Multi-Agent Systems: Building Transparent Reasoning Architectures
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"Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning" — at http://
amzn.to/448dSiA v/ @PacktDataML 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
Develop memory models to retain short-term and -
Practical Guide to Reinforcement Learning from Human Feedback
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New release from @PacktDataML available at http://
amzn.to/3PMn1ZL A Practical Guide to Reinforcement Learning from Human Feedback (RLHF). Amazon Summary: RLHF is a powerful approach to AI alignment and human-centered machine learning. By combining reinforcement learning -
Graph Machine Learning Advancements with PyTorch Geometric Techniques
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Graph Machine Learning — Latest advancements in Graph Data to build robust Machine Learning algorithms (2nd Edition) — at http://
amzn.to/45Y3LyI v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Master new graph ML techniques through updated examples using PyTorch Geometric and Deep -
Intel Joins Terafab Project With Space Hardware Breakthrough
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Remember, @Intel officially joined @ElonMusk
's Terafab project this month. At the same time it unveiled an incredible breakthrough on how to build hardware for space. A fundamental bottleneck to deploying compute in orbit is silicon’s physical vulnerability. In high-radiation -
Multi-Agent AI Systems Design Using MCP Framework
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New release from @PacktDataML available at: http://
amzn.to/40Sp4O9 "Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based Agentic AI Framework with tool use, memory, and multi-agent workflows" Table of Contents:
Introduction to Generative AI and AI