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Getting into data science after the pandemic

Mlearning.ai

I’ve been on this journey for three years now, on my own, learning everything on the internet using this very platform as a reference for a lot of learning too. Fast changes, cautious decisions I’m writing this short text to clarify some of my views on the area, and some of the changes that lead me to my choices for this year.

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Prompt Engineering

Heartbeat

An introduction to “the career of the future” Introduction In just five days, ChatGPT managed to exceed one million users, a feat that took Netflix 3.5 Just two months after OpenAI introduced ChatGPT, the number of monthly users reached 100 million, a remarkable feat! years, Facebook ten months and Instagram two months.

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Improving your LLMs with RLHF on Amazon SageMaker

AWS Machine Learning Blog

Gone are the days when you need unnatural prompt engineering to get base models, such as GPT-3, to solve your tasks. As a method, RLHF requires that you must first train a reward model that reflects human preferences. An important caveat of RLHF is that it is a complex and often unstable procedure. a written email).

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Can society adjust at the speed of artificial intelligence?

Flipboard

Karnofsky, in my view, should get a lot of credit for his prescient views on AI. In the last few years, he’s started to write about the case that AI may be an unfathomably big deal — and about what we can and can’t learn from the behavior of today’s models. There’s a lot of science fiction about this. Star Trek future overnight?

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

Knowledge Bases for Amazon Bedrock automates synchronization of your data with your vector store, including diffing the data when it’s updated, document loading, and chunking, as well as semantic embedding. RAG is a popular technique that combines the use of private data with large language models (LLMs).

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Stress Free Goal Setting with Deb Eckerling

Data Science 101

Hi, thank you so much for having me and I have to tell you this is the first time I’ve been introduced with both of my college affiliation. Now I’ve been coaching and leading groups and helping people define, plan and achieve their goals for years. Fit my days worked out. Connect with Deb.

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Information extraction with LLMs using Amazon SageMaker JumpStart

AWS Machine Learning Blog

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. What makes LLMs so transformative, however, is their ability to achieve state-of-the-art results on these common tasks with minimal data and simple prompting, and their ability to multitask.

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