How To Mitigate Class Imbalance

Original Source Here In the previous blog post, I’ve discussed about what and why of class imbalance, and I have briefly touched upon the solutions for class imbalance. Now, we’ll deep dive into solving class imbalance problem with proposed solution from previous blog post. Resampling Resampling strategies for imbalanced datasets: Kaggle Resampling’s idea is toContinue reading “How To Mitigate Class Imbalance”

[Paper Review] VAE

Original Source Here 휴먼스케이프 Software engineer Covy입니다. 본 포스트에서는 이전에 포스트한 논문 리뷰인 StackGAN의 Conditioning Augmentation Layer 에서 conditioning vector 를 만들어내는 과정의 근원이 되는 논문에 대해서 리뷰하려고 합니다. 리뷰하려는 논문의 제목은 다음과 같습니다. “Auto-Encoding Variational Bayes” 논문에 대한 내용을 직접 보시고 싶으신 분은 이곳을 참고하시면 좋습니다. Objective 논문의 배경은 사전 확률 분포를 학습하기 위해Continue reading “[Paper Review] VAE”

Neural Networks and its Use Cases

Original Source Here Neural Networks and its Use Cases In the past 10 years, the best-performing artificial-intelligence systems — such as the speech recognizers on smartphones or Google’s latest automatic translator — have resulted from a technique called “deep learning.” Deep learning is in fact a new name for an approach to artificial intelligence calledContinue reading “Neural Networks and its Use Cases”

A journey through Neural Networks (Part 0) —Fast Introduction to Linear Algebra

Original Source Here To do the dot product (matrix multiplication) of 2 matrices, the number of column in the first matrix must match the number of rows in the second matrix. This means that in case of non-squared matrices (aka. matrix of size 2×2, 3×3, …, n×n), one of them must be transposed. Remember thatContinue reading “A journey through Neural Networks (Part 0) —Fast Introduction to Linear Algebra”

Transformer in Transformer

Original Source Here Transformer in Transformer Transformer is a type of neural network mainly based on self-attention mechanism . Transformer is widely used in the field of natural language processing (NLP), e.g., the famous BERT and GPT3 models. Inspired by the breakthrough of transformer in NLP, researchers have recently applied transformer to computer vision (CV)Continue reading “Transformer in Transformer”

How handling missing data inappropriately leads to biased ML models

Original Source Here In this article, we’ll do a complete case analysis to learn what happens when we don’t deal with missing data appropriately. We’ll look at a dataset of patients containing features patient ID, age, and BP to build a prognostic model to predict the 10 year risk of death. Dataset of patients withContinue reading “How handling missing data inappropriately leads to biased ML models”

10 Applications that Require Deep Learning

Original Source Here 10 Applications that Require Deep Learning This article is too short. It can’t even begin to describe the ways in which deep learning will affect you in the future. Consider this article to be offering a tantalizing tidbit — an appetizer that can whet your appetite for exploring the world of deepContinue reading “10 Applications that Require Deep Learning”

Pedestrian detection and count for certain number of frames in a video

Original Source Here Contents: Literature Survey Pipeline for working Data Preparation Preprocessing Models Training using pre-trained models on a custom dataset Evaluation of the models trained on custom dataset Making the Flask deployment for the model Output Future Work References Literature Survey: There are many solutions to this problem and basic flow of working whichContinue reading “Pedestrian detection and count for certain number of frames in a video”

Indian Currency Notes Classifier — on cAInvas

Original Source Here Indian Currency Notes Classifier — on cAInvas Classifying Indian currency notes using their images and deep learning. Photo by Alexander Barton for NJI Media on Dribbble Currency notes have identifiers that allow the visually impaired to identify them easily. This is a learned skill. On the other hand, classifying them using imagesContinue reading “Indian Currency Notes Classifier — on cAInvas”