LLM Engineer's Handbook — Master the art of engineering Large Language Models #LLMs from concept to production: http://
amzn.to/4dUQrv6 v/ @PacktDataML Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine with the help of hands-on
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LLM Engineer’s Handbook — Build and Train Large Language Models
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@testingcatalog — 2026-02-15
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2. SSH tunnel Claude Code can now connect to a remote environment via an SSH tunnel. You can literally connect Claude Code to fix your bugs in production! P. S. Don't do that, obviously
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@testingcatalog — 2026-02-15
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Latest Claude desktop updates 1. Commands Claude Code on desktop now supports / commands. Commands are prompt snippets that can be executed across Claude Code and Claude Cowork.
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Impressive coding results in AI development
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Coding results look impressive too. Anyone tried this yet?
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Firecrawl: Open-Source Web Data API for AI
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Sharing a library from the Firecrawl family: "crawler + rendering + parsing + extraction" — the entire chain packaged into a Web Data API for AI use. Open-source, self-deployable, with 82K stars on GitHub. This library mainly converts entire websites into LLM-ready markdown or
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Industry-ready Time Series Forecasting with Python and PyTorch
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Modern #TimeSeries #Forecasting with #Python — Industry-ready #MachineLearning and #DeepLearning time series analysis with PyTorch and PANDAS: http://
amzn.to/4eP5yYt v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Apply ML and global models to improve forecasting accuracy through -
Book: Hands-on Guide to Building AI Agents
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AI Agents in Action: http://
amzn.to/44kbHsL v/ @ManningBooks Gain hands-on experience in these areas: Understand & implement AI agent behavior patterns Design & deploy production-ready intelligent agents Leverage the OpenAI Assistants API and complementary tools -
Build a Text-to-Image Generator from Scratch
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Hot New Release >> Build a Text-to-Image Generator (from Scratch), with transformers and diffusions: http://
amzn.to/3MFbyK4 by @mark_h_liu v/ @ManningBooks -
Designing Machine Learning Systems for Production
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Designing #MachineLearning Systems — An Iterative Process for Production-Ready Applications: http://
amzn.to/46epLSi by @chipro — 𝓣𝓸𝓹𝓲𝓬𝓼:
Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing, -
Practical AI workflow for coding with Opus and Codex
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Interestingly I like vibe coding stuff with opus then bringing in codex to refactor and build further – haven’t had issues yet