Marktechpost

MAY 30, 2024

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.

Artificial Intelligence 132

Artificial Intelligence Artificial Intelligence BERT Computer Vision 132

Towards AI

SEPTEMBER 22, 2023

As an AI practitioner, how do you feel about the recent AI developments? Besides your excitement for its new power, have you wondered how you can hold your position in the rapidly moving AI stream? One example is prompt engineering. Prompt engineering has proved to be very useful.

Prompt Engineer 59

Prompt Engineer Prompt Engineering LLM ML Engineer 59

AWS Machine Learning Blog

SEPTEMBER 1, 2023

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. These users need strong end-to-end ML and data science expertise and knowledge of model deployment and inference.

Generative AI 123

Generative AI Prompt Engineer Prompt Engineering AI 123

Snorkel AI

MAY 4, 2023

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

Snorkel AI

MAY 4, 2023

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

Heartbeat

OCTOBER 5, 2023

To minimize project lifecycle friction and bridge the gap between developers and operations teams. Feature Engineering and Model Experimentation MLOps: Involves improving ML performance through experiments and feature engineering. LLMOps: LLMs excel at learning from raw data, making feature engineering less relevant.

Large Language Models 52

Large Language Models DevOps Prompt Engineer Prompt Engineering 52

AWS Machine Learning Blog

MAY 9, 2024

These encompass a holistic approach, covering data governance, model development, ethical deployment, and ongoing monitoring, reinforcing the organization’s commitment to responsible and ethical AI/ML practices. AI/ML Specialist Solutions Architect at AWS, based in Virginia, US. Vikram Elango is a Sr.

ML 125

ML Generative AI AI AI 125