How to select NLP models for text classification with comparison between classical machine learning and deep learning algorithms with cross-validation.

One of the first questions to answer before deploying a model is what is the business risk of deploying this model?

Following is a list of best books on Data Science and Machine Learning which you may refer.

Machine learning (ML) systems promise disruptive capabilities in multiple industries. Building ML systems can be complicated and challenging, however, especially since best practices in the nascent field of AI engineering are still coalescing. Consequentl…

Revisiting a resurging NeurIPS 2015 paper (and 25 best practices more relevant than that for 2020)…

Using Dask for more efficient data processing on local machines…

An extensive overview of text data augmentation techniques for Natural Language Processing…

The top metric at Kubric for the Data Science team is – “How do we reduce the amount of time spent by a designer on doing grunt work?”. We want to eliminate the grunt work that goes into micro-editing and quality checks so that designers can work on the s…

Photo by Kevin Steinhardt When Azeem asked me to give a talk at CogX, he asked me to focus on just a single point that I wanted the audience to take away. A few years ago my priority would have bee…