From Googleβs 43 rules of ML. Rule #4: Keep the first model simple and get the infrastructure right. With some opinions floating in the market, I feel itβs a good time to spark a discussion about this topic. Otherwise, the opinions of the popular will just drown other ideas. Note: I work in NLP and these opinions are more focussed towards NLP applications. Cannot … [Read more...] about Why Choosing a Heavier NLP Model Might Be a Good Choice?
NLP Interview Questions
Are you hiring technical AI talent for your company? Post your openings on the TOPBOTS jobs board (go to jobs board) to reach thousands of engineers, data scientists, and researchers currently looking for work. It's one thing to practice NLP and another to crack interviews. Giving an interview for NLP role is very different from a generic data science profile. In just a … [Read more...] about NLP Interview Questions
Semantic Search: Theory And Implementation
It took me a long time to realise that search is the biggest problem in NLP. Just look at Google, Amazon and Bing. These are multi-billion dollar businesses possible only due to their powerful search engines. My initial thoughts on search were centered around unsupervised ML, but I participated in Microsoft Hackathon 2018 for Bing and came to know the various ways a … [Read more...] about Semantic Search: Theory And Implementation
An Ultimate Guide To Transfer Learning In NLP
Natural language processing is a powerful tool, but in real-world we often come across tasks which suffer from data deficit and poor model generalisation. Transfer learning solved this problem by allowing us to take a pre-trained model of a task and use it for others. Today, transfer learning is at the heart of language models like Embeddings from Language … [Read more...] about An Ultimate Guide To Transfer Learning In NLP
Productionizing NLP Models
Problem statement π° Lately, I have been consolidating my experiences of working in different ML projects. I will tell this story from the lens of my recent NLP project to classify phrases into categories β A multiclass single label problem. Team structure πͺ Making AI teams is quite tricky. If you donβt have the skillsets inside your company, you have to plan … [Read more...] about Productionizing NLP Models