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Avatar

Sai Sharanya Nalla

Principal Data Scientist at Nike

New York, US

Joined Apr 2024

https://linktr.ee/sharanyanalla

About

Sai Sharanya Nalla is a seasoned Full Stack Data Science leader with a strong academic background in Computer Science and over a decade of experience working at top brands like Amex, AWS and Nike. She excels in leading teams to develop and implement AI and ML solutions at scale. As a leader, she drives product strategy, roadmap development, system design, and cross-functional collaboration to deliver innovative outcomes. Sai is committed to community service, mentoring young students and women in STEM, and contributing to AI conferences with over 1000 audience as a speaker and thought leader. She won Inference 2.0 AI Visionary award and served as a judge at several Hackathons and at Globee Awards. Additionally, she advises tech startups as an AI advisor to a venture capital firm and writes tech blogs to educate and inspire others about AI's potential and practical applications

Stats

Reputation: 354
Pageviews: 9.2K
Articles: 5
Comments: 0
  • Articles

Articles

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A Beginner's Guide To Deploying Hugging Face Models on SageMaker: Unlocking AI Capabilities for NLP, CV, and Gen AI
Learn how to elevate your SageMaker endpoint for any Hugging Face model to run your GenAI or traditional Machine Learning models.
May 16, 2024
· 708 Views · 3 Likes
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Monte Carlo Simulations at Scale: Stock Price Prediction
Learn how to use AWS Batch to run Monte Carlo simulations efficiently and at scale, with a practical example from the financial sector (stock price prediction).
May 13, 2024
· 1,530 Views · 4 Likes
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Convert Your Code From Jupyter Notebooks To Automated Data and ML Pipelines Using AWS
Learn how to convert your code from Jupyter Notebooks into scripts and build automated data and ML pipelines using AWS Glue and Amazon SageMaker.
May 11, 2024
· 3,642 Views · 4 Likes
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Optimize Your Machine Learning Batch Inference Jobs Using AWS
Learn how to optimize your data and ML batch processing jobs using AWS services like AWS Batch, Amazon FSx for Lustre, Amazon ECR, and S3.
May 10, 2024
· 1,204 Views · 4 Likes
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Explainable AI: Interpreting BERT Model
Learn how explainable AI techniques like Integrated Gradients can be used to make a deep learning NLP model interpretable.
May 6, 2024
· 2,106 Views · 5 Likes

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