Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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๐Ÿ“ข 5-Day Generative AI Intensive Course with #Google is now available as a self-paced Learn Guide!

Access whitepapers, podcasts, code labs, & recorded livestreams. Additionally, there is a bonus assignment for you!
https://www.kaggle.com/learn-guide/5-day-genai

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In DS or AI/ML interviews, you need to be able to explain models, debug them live, and design AI/ML systems from scratch. If you canโ€™t demonstrate this during an interview, expect to hear, โ€œWeโ€™ll get back to you.โ€

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She designed proper documentation/a book for common ML interview questions.

Target Audiences: ML engineer, a platform engineer, a research scientist, or you want to do ML but donโ€™t yet know the differences among those titles.Check the comment section for links and repos.

๐Ÿ“Œ link:
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Stop searching for generative AI resources one category at a time. ๐Ÿš€

Awesome Generative AI is a curated directory of generative AI projects and services for builders exploring the ecosystem. ๐ŸŒ

It helps you compare where to look next by organizing links and short descriptions across models, tools, agents, media, and learning resources. ๐Ÿ“Š

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โ€ข Text stack โ€“ browse models, chatbots, search engines, writing tools, research tools, and leaderboards โœ๏ธ
โ€ข Coding toolkit โ€“ find coding assistants, developer tools, playgrounds, and local LLM deployment options ๐Ÿ’ป
โ€ข Agent directory โ€“ scan autonomous agent projects and custom assistant resources ๐Ÿค–
โ€ข Multimodal map โ€“ explore image, video, audio, and music tools in dedicated sections ๐ŸŽจ๐ŸŽต
โ€ข Learning library โ€“ use recommended reading, milestones, courses, guides, and related lists to build context ๐Ÿ“š

Itโ€™s open-source (CC0-1.0 license). ๐Ÿ”“

Repo: https://github.com/steven2358/awesome-generative-ai

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