Convex Optimization (#1 best-seller in Linear Programming): http://
amzn.to/40gXKZA Comprehensive introduction to the subject, this book shows how such problems can be solved numerically with great efficiency. Solutions are applicable to many fields: engineering, computer
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Convex Optimization: Essential Linear Programming Resource for AI
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Practical Linear Algebra for Data Science with Python Applications
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Practical Linear Algebra for #DataScience — From Core Concepts to Applications Using #Python — http://
amzn.to/3WWJKR4
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#DataScientist #AI #ML #MachineLearning #Mathematics #LinearAlgebra #Coding -
Syllabus to Learn Python Programming for ML and AI
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Syllabus to learn python programming http://
amzn.to/44Ke9ZK #Syllabus #python #programming #MachineLearning #AI #IoT -
StepWiser: Stepwise Generative Judges for Wiser Reasoning
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What if we apply RL+Reasoning into PRMs? StepWiser: Stepwise Generative Judges for Wiser Reasoning STEPWISER trains a CoT-based judge that checks whether each “chunk-of-thought” helps solve the problem, producing better step labels and stronger search than discriminative PRMs
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Google Engineer Releases Free Agentic Design Patterns Book
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This Google engineer just released a 424-page free book on Agentic Design Patterns. Covers advanced prompt engineering, multi-agent frameworks, RAG, agent tool use and MCP. 100% free with practical code examples.
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Grok Code Releases Improved Updates Every Two Days
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Grok Code ships improved updates every 2 days, so you should notice rapid improvement
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DeepMCPAgent: Dynamic MCP Tool Discovery and Agent Development
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DeepMCPAgent A powerful tool for dynamic MCP tool discovery and agent development. Built with LangChain and LangGraph, it streamlines integration over HTTP/SSE while supporting major LLMs. Check it out! https://
github.com/cryxnet/deepmc
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Groq Showcases Kimi and Claude Code Integration Cooking
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You love to see it. Cooking with Kimi and Claude Code on @GroqInc
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Simple message storage approach without LangGraph framework
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Uh I have been doing this for many years now. I have no need to run to langgraph. Step 1: place messages in db Step 2: pull messages from db There is no step 3 haha
