Autosuggestion, also known as query autocompletion (QAC), predictive search, and type-ahead, is a key search-assist feature that has become indispensable in modern information retrieval for enhancing search experience. …

Efficient tracking and monitoring of Transformer models for Financial Sentiment Analysis using MLFoundry, by TrueFoundry — Natural language processing (NLP) has become increasingly popular in financial applications in recent years. Stock/forex market forecasting, volatility modeling, asset allocation, business taxonomy construction, credit scoring, initial public offering (IPO) valuation, and other applications are among them. One common task (or rather subtask, which can provide features for some tasks…

PyTorch implementation of VQA models using text and image transformers from Hugging Face — Recent years have seen significant advancements not only in the respective domains of Natural Language Processing (NLP) and Computer Vision (CV) but also in tasks involving multiple modalities (text + image features) such as image captioning, visual question answering (VQA), cross-modal retrieval, visual common-sense reasoning, and more. …

Over the last 3 posts, we developed a firm understanding of how to version ML artifacts & build ML Pipelines with great ease & sophistication. By now, you should be reasonably familiar with tracking your data using DVC & experimenting with various ML models for regression & classification tasks by…

In Part 2 of this 4-blog series, we gained some experience with DVC, a tool to implement efficient versioning of ML artifacts. With our data in place, the next steps in an ML workflow are to first perform EDA, followed by feature engineering & model training. …

In Part 1 of this 4-blog series, we understood the motivation behind adopting MLOps practices & also looked at some of the basic principles of MLOps. We also had a glance at the arsenal of tools & frameworks used to implement MLOps in various stages of an ML workflow lifecycle…

Ever wondered how organizations build, deploy, maintain, adapt, retrain and redeploy large-scale AI-powered applications? In today’s fast-paced industry, maintaining and deploying scalable applications while being able to adapt quickly to the changing consumer requirements is of utmost importance. Through this 4-blog series on Fundamentals of MLOps, you will be introduced…

Wrapping Up GSoC 2020! This summer has truly been one of the most eventful summers for me till date, packed with some awesome learning experience coming my way as a part of Google Summer of Code 2020 😄 ! This is a wrap up post, discussing all the work I have done over this…