Author: Vinitha V N

A Chatbot Application by finetuning GPT

You might have seen chatbots in many customer services. Have a look at a similar kind of bot here.  How do these bots respond to user queries? How does this bot understand the user’s intention and give smart responses? In this blog, we are going to build the above smart chatbot by leveraging machine learning […]

LSTM to Transformers

Transformer models has become the go-to model in most of the NLP tasks. Many transformer-based models like BERT, ROBERTa, GPT series, etc are considered as the state-of-the-art models in NLP. While NLP is overwhelming with all these models, Transformers are gaining popularity in Computer vision also. Transformers are now used for recognizing and constructing images, […]

Transformer Based Models

Transformer models have achieved a significant milestone in the field of NLP. Not only in the field of NLP, but also in Computer Vision, we can see Transformer models outperforming all the so-called state-of-the-art models. Transformers have been proven to improve long-term dependencies and can be used to leverage the technique called Transfer learning, which […]

The Power Of Transfer Learning

Introduction If you are familiar with machine learning, particularly deep learning, you might have heard of the term transfer learning. What is transfer learning? In this blog, we are going to discuss about Need for transfer learning What is transfer learning How to use transfer learning Benefits and limitations of transfer learning Need for transfer […]

Error Metrics in Machine learning

Introduction If you are reading this blog, you will probably be familiar with machine learning or will be interested in learning the same. Machine learning is a subfield of artificial intelligence, where it makes the systems to learn from data and make them capable of taking decisions with minimal human intervention. Now generally, we use […]

Case Study: Defect Detection in Products using Image Segmentation

Table of contents Introduction Problem statement ML formulation Performance Metric Understanding the data Data Preparation Modeling Training Prediction of segmentation maps on test data Future Works References 1. Introduction What is Object Detection? Given an image, we humans can identify the objects present in that image. For example, we can detect whether the image has […]

Case Study: Medical Report Generation Using Deep Learning

Table of Contents Overview Prerequisites Business Problem Data Analysis ML Formulation Performance Metric Data preparation Modeling Comparison of models Model Deployment Future Works Profile References 1. Overview Image captioning is one of the most important and challenging tasks in deep learning. It is the process of generation of a textual description for an image. For […]

Case Study: Reducing Commercial Aviation Fatalities

Table of Contents Overview Business Problem Dataset Analysis Mapping the Real Problem into ML problem Performance Metric Exploratory Data Analysis Feature Engineering Data preprocessing Modeling Future improvements Results References Overview Source: https://www.kaggle.com/c/reducing-commercial-aviation-fatalities This was a competition conducted by Kaggle where we needed to build a model to detect troubling events from aircrew’s physiological data. Aviation […]