Transformer models have 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…

Introduction Neural networks are designed to mimic the behavior of human brains, to understand various relationships in the data. These networks have the power to understand complex non-linear relationships and can help us to make more intelligent decisions. Neural networks are used in fields like image processing, natural language processing, etc…

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…

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…

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…

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. …

What is Logistic regression? Logistic regression is a simple classification algorithm where the output or the dependent variable is categorical. For example: To classify an email into spam or not spam To predict whether a patient has cancer or not Logistic regression uses a logistic function for this purpose and hence the name. This…

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 need to build a model to detect troubling events from aircrew’s physiological data.