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
Technical Guide
Who Is Your Golden Goose? Learn With Cohort Analysis
Customer segmentation is the technique of diving customers into groups based on their purchase patterns to identify who are the most profitable groups. In segmenting customers, various criteria can also be used depending on the market such as geographic, demographic characteristics or behavior bases. This technique assumes that groups with different features require different … [Read more...] about Who Is Your Golden Goose? Learn With Cohort Analysis
Better Sentiment Analysis with BERT
Imagine you have a bot answering your clients, and you want to make it sound a little bit more natural, more human.To achieve that, you have to make the answers more personalized. One way to learn more about the customers you’re talking to is to analyze the polarity of their answers. By polarity here I mean detecting if the sentence (or group of sentences) is written with … [Read more...] about Better Sentiment Analysis with BERT
Top AI & ML Research Trends For 2020
The AI industry is moving so quickly that it’s often hard to follow the latest research breakthroughs and achievements. To help you stay well prepared for 2020, we have summarized the latest trends across different research areas, including natural language processing, conversational AI, computer vision, and reinforcement learning.We also suggest key research papers in … [Read more...] about Top AI & ML Research Trends For 2020
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
TOPBOTS Guide To NeurIPS 2019
This year’s Annual Conference on Neural Information Processing (NeurIPS 2019) will be held in Vancouver, Canada from December 8th to 14th, 2019. The popularity of this conference is growing rapidly, with the number of submitted papers getting to the record-breaking number of 6743, almost 40% more than last year.The TOPBOTS team is also going to NeurIPS again this year. To … [Read more...] about TOPBOTS Guide To NeurIPS 2019
Productionizing NLP Models
Problem statement 💰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 — A multiclass single label problem.Team structure 👪Making AI teams is quite tricky. If you don’t have the skillsets inside your company, you have to plan … [Read more...] about Productionizing NLP Models
A Step-By-Step Guide On Deploying A Machine Learning Model
One the key ways that a data scientist can provide value to a startup is by building data products that can be used to improve products. Making the shift from model training to model deployment means learning a whole new set of tools for building production systems. Instead of just outputting a report or a specification of a model, productizing a model means that a data science … [Read more...] about A Step-By-Step Guide On Deploying A Machine Learning Model
What’s State Of The Art In AutoML in 2019?
More and more industries and organizations are leveraging artificial intelligence to delight customers and cut through the competition. However, development and deployment of deep learning models is time-consuming and costly - often prohibitively costly. That’s when automated machine learning (AutoML) comes into play. AutoML solutions can significantly increase the efficiency … [Read more...] about What’s State Of The Art In AutoML in 2019?
Overview of the Different Approaches to Putting Machine Learning Models in Production
There are different approaches to putting models into production with benefits that can vary dependent on the specific use case. Take, for example, the use case of churn prediction. It is beneficial to have a static value that can be easily looked up when someone calls customer service, but there is some extra value that could be gained if, for specific events, the model could … [Read more...] about Overview of the Different Approaches to Putting Machine Learning Models in Production