Pranjal KhadkaInformation TheoryInformation Theory plays a critical role in Machine Learning by quantifying the information present in a dataset. Entropy is a key term…6d ago6d ago
Pranjal KhadkaProbability TheoryEvery machine learning applications have to deal with uncertainty because we can never build a perfect system that can predict correct…Aug 31Aug 31
Pranjal KhadkainGoPenAIPaper Breakdown : U-Net (Convolutional Networks for Biomedical Image Segmentation)U-Net is one of the most influential paper in the field of Image segmentation. It came out around 2015 by researchers from University of…Jul 24Jul 24
Pranjal KhadkaUnderstanding Convolutional Neural Network (CNNs)Convolutional Neural Networks (CNNs) also commonly referred to as ConvNets was introduced around 2012 to address the challenges associated…Jul 18Jul 18
Pranjal KhadkaLinear Algebra for Machine Learning : Part 2In the last part of this series, “Linear Algebra for Machine Learning,” we explored various foundational topics such as linear…Jul 13Jul 13
Pranjal KhadkaLinear Algebra for Machine Learning : Part 1Linear Algebra is one of the most fundamental topics when starting out in Machine Learning. Linear algebra is the study of numbers…Jul 10Jul 10
Pranjal KhadkaGPT 1 explained !This is a breakdown of the paper “Improving Language Understanding by Generative Pre-Training” by OpenAI. While unlabeled textual data are…Jul 4Jul 4
Pranjal KhadkaCase Study : Machine Learning Operations by IBMThis is a breakdown of the paper “Machine Learning Operations (MLOps): Overview, Definition, and Architecture” published by IBM Germany…Jun 28Jun 28
Pranjal KhadkaCase Study : Uber’s Machine Learning Platform “Michelangelo”Michelangelo is an internal ML-as-a-service platform at Uber that democratizes machine learning and makes scaling AI to meet the needs of…Jun 22Jun 22
Pranjal KhadkaA Journey from RNNs to LSTMs to XLSTMsTraditionally neural network were designed to work with vectors or images all of which do not have any sequence. But, what do we do if we…Jun 13Jun 13
