Books/resources for GenAI?

Hey everyone, As the title suggests, I'm looking for resources to learn ML/AI just for the sake of learning, and potentially doing projects of my own with the knowledge I learn. I'd appreciate any responses on the same! Background: Product. I try and learn about engineering stuff regularly. :)

Hello all, I am a 2023 graduate and started my job around 2 months ago in the data science field. Everything is going ok till now but now I want to go deep into the data science field as I am feeling that I am not learning enough. I am currently working in the NLP field, any suggestions on what courses can be done or what topics to explore more from the experienced folks would be helpful. Any course suggestions that explain concepts from scratch to intermediate or advanced level are welcome (paid or free) Thanks 😊 ( Reposted from my own post in the Software Engineer Community)

There's so much happening every day. I never really like the AI/ML courses of college (lol) but want to actually try the new stuff now. What'd you say is the best way of at least knowing the basics of whatever comes up daily? I know I could just google (and I will), curious to know if y'all know of something which defines the base vocabulary needed to actually understand the daily breakthroughs. Few things I've been meaning to know more about - RLHF - Fine tuning (what and how) - LLM structure (should have kept up with LLM basics but I didn't lol, pls share stuff) - LoRA/QLoRA (?? idk lmao) - RAG (vectorisation of inputs + cosine similarity with query?) - Mamba architecture (1. what, saw on twitter, no idea) Currently downloading https://ollama.ai/ to try running llama locally. Any links/pointers/newsletter archives appreciated

With a lot of things and hype around AI, I am having real FOMO. I want to start learning about AI and planning to do some mini projects involving the latest LLMs and Other AI library. Could anyone suggest plan or resources on How do I start my journey in AI and learn generative AI

Hey guys, I want to revise my ML & DL concepts and would like to know if anyone knows good references/sources to revisit the concepts I want to cover the algorithms in fundamental depth rather than just application of models ( ex : difference between gradient descent / ols regressions When to use beta in classifications when looking at f score etc. what is the difference between acf/pacf in time series Can someone suggest good sources where I can go through such concepts in depth? )

Hi guys, I am a Backend Engineer, with the evolving trends in AI and ML , I want to make myself familiar with things like Machine Learning, Deep Learning and LLM stuff. would appreciate free resources or a path. Thanks 🙏 Also do share your experience moving into these domains.

I am an ML enthusiast and have been learning Reinforcement Learning and other Algorithms to shift my profile to ML engineer. But as soon as I started applying for jobs, every job is looking for people who have experience in GENAI, LLMs, etc. So I want to know, how can I become one?

Can you please suggest a course/videos to learn Gen AI ?