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Large Language Models: A Self-Study Roadmap

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I have given a few resources that might help you learn NLP: Coursera: DeepLearning.AI Natural Language Processing Specialization - Focuses on NLP techniques and applications (Recommended) Stanford CS224n (YouTube): Natural Language Processing with Deep Learning - A comprehensive lecture series on NLP with deep learning.

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AWS Machine Learning: A Beginner’s Guide

How to Learn Machine Learning

Remember, your journey into machine learning doesn’t have to be overwhelming AWS provides the structure and support to help you succeed at every step. External Links: AWS Machine Learning Documentation ( [link] ) AWS ML Blog ( [link] ) AWS Training and Certification ( [link] ) Thank you for reading!

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Life beyond the leaderboard

DrivenData Labs

competition, winning solutions used deep learning approaches from facial recognition tasks (particularly ArcFace and EfficientNet) to help the Bureau of Ocean and Energy Management and NOAA Fisheries monitor endangered populations of beluga whales by matching overhead photos with known individuals.

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Using LLMs to fortify cyber defenses: Sophos’s insight on strategies for using LLMs with Amazon Bedrock and Amazon SageMaker

AWS Machine Learning Blog

We have defined three specialized tasks that are covered later in the blog. Our analysis in this blog post has focused on Anthropic’s Claude 3 Sonnet model and three specific use cases. In this blog we covered the experimentation phase. This blog covers how to build guardrails in your generative AI applications.

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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

In this blog post, we walk you through how to deploy and prompt a Llama-4-Scout-17B-16E-Instruct model using SageMaker JumpStart. Efficiency and Productivity Gains**: - **Content Generation**: LLMs can automate the creation of various types of content, such as blog posts, reports, product descriptions, and social media updates.

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Streamlining Process Configuration in Machine Learning with Hydra

Pickl AI

As the global Machine Learning market, valued at USD 35.80 billion in 2022, is expected to soar to USD 505.42 This blog highlights the importance of organised, flexible configurations in ML workflows and introduces Hydra. These issues can hinder experimentation, reproducibility, and workflow efficiency.

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Revolutionizing Compliance: The Promise of Graph RAG-Based Large Language Models

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billion on compliance in 2022 (up 19% from 2020) — costs that continue to rise despite limited improvements in effectiveness [3]. Serving as both a Cloud Architect and an AI practitioner-researcher, he possesses extensive expertise in cloud-native architectures, serverless computing, data and analytics, deep learning, and generative AI.

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