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In this blog, I explore the critical step of deploying AI models using REST API, emphasizing the transition from controlled environments to real-world applications. The post details the use of Python, Flask, and Keras to create a REST API for a pre-trained VGG16 model, enabling predictions on images. I also provide instructions for testing the API and highlight the potential for global accessibility when deployed on cloud services with GPU support. The complete source code is available on GitHub for reference.

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In this blog post, you will discover how to take an image and generate permutated versions of it. Each permutated image will conceal a specific region from the original image. By observing the change in output probability resulting from the removal of these regions, you will gain insight into the significance of each region in the prediction process.

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In this blog post, you will understand various techniques to Fine-Tune Large Language models on Custom Datasets. The Article shall cover different techniques and their trade-offs. In the end, we conclude with the most optimal approach and programming framework to perform that task.

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