Authoring

Authoring

Below are the blogs, articles, and tutorials I have written on Machine Learning, Deep Learning, and MLOps. I am fortunate to collaborate with many talented individuals globally and share my knowledge with the community.

Weights & Biases

Featured Articles

• Hyperparameter Optimization with Weights & Biases Sweeps
• Multimodal Few-Shot Learning with Frozen Language Models

Reports & Tutorials

• Introduction to Image Inpainting with Deep Learning (joint work with Sayak Paul)
• Understanding the Effectiveness of Ensembles in Deep Learning (joint work with Sayak Paul)
• Unsupervised Visual Representation Learning with SwAV (joint work with Sayak Paul)
• Benchmarking the 🤗 Transformers for Tensorflow 2
• Visualize Class Activation Maps for Image Classification Models
• Reproducible Models with W&B
• Keras XLA Benchmarks (in collaboration with Soumik Rakshit and Sayak Paul)
• Visualize Models in TensorBoard with Weights & Biases
• Visualizing Model Performance with W&B
• Building LLM Evaluation Frameworks
• MLOps for Computer Vision Systems

Medium Articles

I regularly publish technical articles on Medium, covering various aspects of machine learning, deep learning, and MLOps:

• Building Robust LLM Applications
• The State of LLM Evaluation
• Machine Learning System Design: A Comprehensive Approach
• Gradient Amplification Attack: Circumventing Defenses Against Backdoor Attacks
• Training with Mixed Precision in TensorFlow 2.0

Tutorials & Guides

I’ve created in-depth tutorials on various ML/DL topics:

• TensorFlow Implementation of SwAV - GitHub repository with detailed notebooks
• LLM Evaluation Strategies - Repository demonstrating systematic LLM evaluation approaches
• E2E MLOps Pipeline on GCP for Tensorflow - End-to-end MLOps on Google Cloud Platform

Collaborative Work

I enjoy collaborating with other practitioners in the field:

• Open Source Contributions: I build MLOps pipelines for popular repositories like Keras, OpenMMLab, and Meta
• Technical Reviews: I provide technical reviews for ML/DL content published by various platforms