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Category Archives: Machine Learning

Linear mapping  Let V and W are the vector spaces over field K. A function f: V-> W is said to be the linear map… Read More
Before jumping into the term “Data Analysis”, let’s discuss the term “Analysis”. Analysis in Layman’s language (Plain English) is a process of answering “How?” and… Read More
In linear or multiple regression, it is not enough to just fit the model into the dataset. But, it may not give the desired result.… Read More
Beta Variational Autoencoders was proposed by researchers at Deepmind in 2017. It was accepted in the International Conference on Learning Representations (ICLR) 2017. Before learning… Read More
The goal of contrastive learning is to learn such embedding space in which similar samples are close to each other while dissimilar ones are far… Read More
True Error The true error can be said as the probability that the hypothesis will misclassify a single randomly drawn sample from the population. Here… Read More
The Singular Value Decomposition (SVD) of a matrix is a factorization of that matrix into three matrices. It has some interesting algebraic properties and conveys… Read More
Affine spaces Affine space Affine space is the set E with vector space \vec{E} and a transitive and free action of the additive \vec{E} on… Read More
XgBoost stands for Extreme Gradient Boosting, which was proposed by the researchers at the University of Washington. It is a library written in C++ which… Read More
Are you a complete beginner to the broad spectrum of Machine Learning? Are you torn between R, Python, GNU Octave, and all the other computer… Read More
In this article, we will use mediapipe python library to detect face and hand landmarks. We will be using a Holistic model from mediapipe solutions… Read More
Variational Autoencoders Variational autoencoder was proposed in 2013 by Knigma and Welling at Google and Qualcomm. A variational autoencoder (VAE) provides a probabilistic manner for… Read More
The basic neural network design i.e. an input layer, few dense layers, and an output layer does not work well for the image recognition system… Read More
Managing the Machine Learning Projects isn’t an easy piece of cake for every ML enthusiast or a student/developer working on them. Even Gartner has concluded… Read More
Due to its simplicity, easy operation, capacity to protect against local optima, and the problem of derivatives free, Metaheuristic was frequently employed throughout the previous… Read More

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