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Part 5: Multi-Modal Synthetic Data Generation with GPT-4, DALL E & Prompt Chaining

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This blog post is Part 5 of  Generative AI in Data Science series. This one tackles multi-modal synthetic data generation combining text, images, and structured data using GPT-4, DALL·E, and prompt chaining. It is built for your audience of data science professionals who care about building real-world, reproducible pipelines.   Part 5: Multi-Modal Synthetic Data […]

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Part 4: Benchmarking Synthetic Data – How Close Is “Close Enough”?

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This is Part 4 of Generative AI in Data Science. Do read previous parts to get a full understanding. In this blog post we will learn about benchmarking synthetic data. This post gives you a practical framework for quantifying the quality and validating the effectiveness of synthetic data for real-world model training.   Part 4:

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Part 3: Automating GPT-Based Synthetic Data Generation for Real World Modeling

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This is Part 3 of the Generative AI in Data Science blog series. This post takes things up a next level automating synthetic data generation across domains, injecting real-world messiness, and generating labeled text data for NLP tasks.   Part 3: Automating GPT-Based Synthetic Data Generation for Real-World Modeling In Part 1and Part 2, we

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Part-2 Building a Synthetic Tabular Data Generator With GPT-4 and Python

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Part 2 of blog series is a deep, code-heavy guide that walks you readers through building and validating a synthetic data generator using GPT-4 + Python. in Part 1 we have already learned the importance of Synthetic data and why it is needed. If you have not read Part 1 yet, Click Here     Goal:

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Variables in C: Simple Explanation With Code Examples

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What is a Variable? In any programming language variables are containers. It is used to store values or data. Values or data can be in the form of numbers or characters. Variables are also called identifiers. It identifies memory locations for different values. We call it variables because it’s values changes as per the programming

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11 MLOps Tools for Machine Learning Engineers to Know

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 Machine Learning is rapidly growing field. We get news of every day new development, new evolution in this field. After Developing ML models we deploy in the production. Deploying models into production efficiently and reliably is job of expert professionals. Machine Learning Operations (MLOPs) provides CI/CD(Continuous Integration/Continuous Development) platforms that bridges the gap between data

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100 AI Interview Questions and Answers: A Easy Guide

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Artificial Intelligence (AI) is rapidly transforming how industries function, making it a hot career path for engineers, data scientists, and developers. Whether you are aiming for a role in machine learning, deep learning, or general AI, preparing for interviews with a solid grasp of core and advanced concepts is key. This comprehensive guide explores 100

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