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Suman Debnath
PhD in Organometallic Chemistry and Catalysis
Suman Debnath is currently serving as a Principal Developer Advocate for Machine Learning at Amazon Web Services (AWS). In this role, he focuses on promoting and facilitating the use of machine learning technologies within the AWS ecosystem, helping developers and organizations leverage these tools effectively.
Professional Background
- Current Position: Principal Developer Advocate, Machine Learning at AWS
- Key Responsibilities:
- Advocating for machine learning solutions within AWS.
- Engaging with developers to enhance their understanding and application of machine learning technologies.
- Leading initiatives to improve the integration of machine learning into various AWS services.
Education
Suman holds a strong academic background that supports his expertise in technology and engineering. His educational credentials include:
- Doctor of Philosophy (PhD) in Electrical and Computer Engineering from Purdue University.
- Dual Degree (BS and MS) in Electrical Engineering from the Indian Institute of Technology, Madras.
Skills and Expertise
Suman Debnath has developed a robust skill set throughout his career, particularly in areas related to:
- Machine Learning
- Cloud Computing
- Developer Advocacy
- Technical Communication
Contributions
In addition to his role at AWS, Suman is known for his contributions to the tech community through various speaking engagements, workshops, and publications aimed at advancing knowledge in machine learning and cloud technologies. His work often emphasizes practical applications and real-world implementations of these technologies.
For more detailed insights into his professional journey, you can view his LinkedIn profile under the username suman-d.
Highlights
🚀 This week, we added a new capability within Knowledge Bases(KB) in Amazon Bedrock, which now allows you to engage with documents directly, providing a real-time and zero-setup method to securely chat with your data.
📂 How It Works:
- Drag & Drop: Simply drag and drop a file, such as a PDF, from your desktop or specify the S3 file path.
- Instant Interaction: Begin chatting with your document immediately.
You can use this functionality both via console and SDK.
https://lnkd.in/eKdZcjTP
✨ Step into this two-part series on the wonders of Vector, Embeddings and RAG, leveraging Amazon Bedrock, Aurora, and LangChain. ✨
🔍 Part 1 peels back the layers on vector embeddings, showing how they're key in machine learning. We share easy-to-follow advice on using Amazon Bedrock and LangChain to harness their power.
🔧 Part 2 guides you through using Amazon Aurora as a vector store for these embeddings, and how it can be teamed up with Amazon Bedrock to supercharge RAG techniques.
🎥 For a visual tour of these concepts, you may like to watch the re:Invent 2023 session on "Utilizing machine learning & vector databases for advanced AI search".
Part 1: https://lnkd.in/gAWTihhz
Part 2: https://lnkd.in/g7ECNGjN
Link: https://lnkd.in/guSB9Tk5
