Suman Debnath, principal developer advocate for machine learning at Amazon Web Services, emphasized the advantages of using Python in machine learning during a New Stack Makers episode recorded at PyCon US. He noted Python's ease of use and its foundational role in the data science ecosystem as key reasons for its popularity. However, Debnath highlighted that building generative AI applications doesn't necessarily require deep data science expertise or Python.
Suman Debnath, principal developer advocate for machine learning at Amazon Web Services, emphasized the advantages of using Python in machine learning during a New Stack Makers episode recorded at PyCon US. He noted Python's ease of use and its foundational role in the data science ecosystem as key reasons for its popularity. However, Debnath highlighted that building generative AI applications doesn't necessarily require deep data science expertise or Python.
Amazon Bedrock, AWS’s generative AI framework introduced in September, exemplifies this flexibility by allowing developers to use any programming language via an API-based service. Bedrock supports various languages like Python, C, C++, and Java, enabling developers to leverage large language models without intricate knowledge of machine learning. It also integrates well with open-source libraries such as Langchain and llamaindex. Debnath recommends visiting the community AWS platform and GitHub for resources on getting started with Bedrock. The episode includes a demonstration of Bedrock's capabilities and its benefits for Python users.
Learn More from The New Stack on Amazon Bedrock:
Amazon Bedrock Expands Palette of Large Language Models
Build a Q&A Application with Amazon Bedrock and Amazon Titan
10 Key Products for Building LLM-Based Apps on AWS
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