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Category Archives: Machine Learning

Topic Modeling: Topic modeling is a way of abstract modeling to discover the abstract ‘topics’ that occur in the collections of documents. The idea is… Read More
Prerequisite: Word2Vec Word Embedding: It is a language modeling technique used for mapping words to vectors of real numbers. It represents words or phrases in… Read More
Introduction: The Jacobian is a very powerful operator used to calculate the partial derivatives of a given function with respect to its constituent latent variables.… Read More
Regularized Discriminant analysis Linear Discriminant analysis and QDA work straightforwardly for cases where a number of observations is far greater than the number of predictors… Read More
Prerequisite: Attention Mechanism | ML A wise man once said, “Manage your attention, not your time and you’ll get things done faster”. In this article,… Read More
Latent Semantic Analysis is a natural language processing method that uses the statistical approach to identify the association among the words in a document. LSA… Read More
Prerequisite: Convolutional Neural Networks Dilated Convolution: It is a technique that expands the kernel (input) by inserting holes between its consecutive elements. In simpler terms,… Read More
Pre-requisite: Separating Hyperplanes in SVM The Lagrange multiplier equation for the support vector machine. The equation of that can be given by: Now, according to… Read More
Contractive Autoencoder was proposed by the researchers at the University of Toronto in 2011 in the paper Contractive auto-encoders: Explicit invariance during feature extraction. The… Read More
In this article, we’ll learn how to implement an XOR gate in Tensorflow. Before we move onto Tensorflow implementation we’ll have a look at how… Read More
In this article, we are going to see how to install TensorFlow in Linux. It is a completely open-source library for numerical computation using data… Read More
In this article, we are going to see how to use Weka explorer to do simple k-mean clustering. Here we will use sample data set… Read More
Odds (odds of success): It is defined as the chances of success divided by the chances of failure. Say, there is a 90% chance that… Read More
In this article, we will see Why TensorFlow Is So Popular, and then explore Tensorflow Features. TensorFlow is an open-source software library. It was originally… Read More
A neural network is a processing device, either an algorithm or genuine hardware, that endeavors to recognize underlying relationships in a set of data through… Read More

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