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Top Artificial Intelligence AI Courses from Google

Marktechpost

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. Participants learn how to improve model accuracy and write scalable, specialized ML models.

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Benchmarking Computer Vision Models using PyTorch & Comet

Heartbeat

[link] Transfer learning using pre-trained computer vision models has become essential in modern computer vision applications. In this article, we will explore the process of fine-tuning computer vision models using PyTorch and monitoring the results using Comet. Pre-trained models, such as VGG, ResNet.

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TOP 20 AI CERTIFICATIONS TO ENROLL IN 2025

Towards AI

Artificial Intelligence graduate certificate by STANFORD SCHOOL OF ENGINEERING Artificial Intelligence graduate certificate; taught by Andrew Ng, and other eminent AI prodigies; is a popular course that dives deep into the principles and methodologies of AI and related fields.

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From concept to reality: Navigating the Journey of RAG from proof of concept to production

AWS Machine Learning Blog

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. For more information on application security, refer to Safeguard a generative AI travel agent with prompt engineering and Amazon Bedrock Guardrails.

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Moderate audio and text chats using AWS AI services and LLMs

AWS Machine Learning Blog

Use LLM prompt engineering to accommodate customized policies The pre-trained Toxicity Detection models from Amazon Transcribe and Amazon Comprehend provide a broad toxicity taxonomy, commonly used by social platforms for moderating user-generated content in audio and text formats. LLMs, in contrast, offer a high degree of flexibility.

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#63: Full of Frameworks: APDTFlow, NSGM, MLFlow, and more!

Towards AI

But who exactly is an LLM developer, and how are they different from software developers and ML engineers? Machine learning engineers specialize in training models from scratch and deploying them at scale. If you are skilled in Python or computer vision, diffusion models, or GANS, you might be a great fit.

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Use your data to build your AI moat: The Future of Data-Centric AI 2023

Snorkel AI

Reinforcement learning has shown great promise in mastering complex games and decision-making tasks, while computer vision has progressed rapidly, allowing for more accurate image recognition, object detection, and scene understanding. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.