Practical Introduction to Hartree-FockLaksh AithaniBlockedUnblockFollowFollowingMay 7We will write a Hartree-Fock algorithm completely from scratch in Python and use it to…

Continue Reading# matrix

## An overview of Principal Component Analysis

How will it look?Variance is the expectation of the squared deviation of a random variable from its mean. Informally, it…

Continue Reading## Singular Value Decomposition vs. Matrix Factoring in Recommender Systems

I had to dig a little bit, but eventually, I found some hidden gems. According to Luis Argerich:The matrix factorization…

Continue Reading## Principal Component Analysis — Math and Intuition (Post 3)

I hope you chose the black line as it is closer to most of the data points (see figure below).…

Continue Reading## Principal Component Analysis — Math and Intuition (Post 2)

Principal Component Analysis — Math and Intuition (Post 2)Shivangi PatelBlockedUnblockFollowFollowingApr 4This is Post 2 of a 3-part series on Principal Component Analysis — Math and…

Continue Reading## Introduction to Convolutional Neural Networks (CNN) with TensorFlow

Introduction to Convolutional Neural Networks (CNN) with TensorFlowLearn the foundations of convolutional neural networks for computer vision and build a…

Continue Reading## Building a Music Recommendation Engine with Probabilistic Matrix Factorization in PyTorch

However, it should be noted that each of these matrices are randomly initialized. Therefore, in order for these predictions and…

Continue Reading## Random forest text classification in R: Trump v. Obama

Random forest text classification in R: Trump v. ObamaCan I successfully determine the differences in speech content between the 2…

Continue Reading## PCA and SVD explained with numpy

PCA and SVD explained with numpyZichen WangBlockedUnblockFollowFollowingMar 16How exactly are principal component analysis and singular value decomposition related and how to…

Continue Reading## How to do Cost-Sensitive Learning

How to do Cost-Sensitive LearningBe right in classification modeling when it matters mostJoe Tenini, PhDBlockedUnblockFollowFollowingFeb 25IntroductionData Science teams must often walk…

Continue Reading## Accuracy Trap! Pay Attention to Recall, Precision, F-Score, AUC

Pay Attention to Recall, Precision, F-Score, AUCHaydar ÖzlerBlockedUnblockFollowFollowingFeb 25The article contains examples to explain accuracy, recall, precision, f-score, AUC concepts. Assume…

Continue Reading## How companies use collaborative filtering to learn exactly what you want

Whether it’s that new set of speakers that you’ve been eyeballing, or the next Black Mirror episode — their use of predictive…

Continue Reading## A Neural Implementation of NBSVM in Keras

A Neural Implementation of NBSVM in KerasArun MaiyaBlockedUnblockFollowFollowingJan 30NBSVM is an approach to text classification proposed by Wang and Manning¹ that…

Continue Reading## A Gentle Introduction to Deep Learning : Part 3

A Gentle Introduction to Deep Learning : Part 3PCA & Linear Algebra(Advance)Akshat JainBlockedUnblockFollowFollowingJan 27Photo by Antoine Dautry“You can’t build great building on a…

Continue Reading## Visualizing Principal Component Analysis with Matrix Transformations

Visualizing Principal Component Analysis with Matrix TransformationsA guide to understanding eigenvalues, eigenvectors, and principal componentsAndrew KrugerBlockedUnblockFollowFollowingJan 20Principal Component Analysis (PCA)…

Continue Reading## How to do Deep Learning on Graphs with Graph Convolutional Networks

How to do Deep Learning on Graphs with Graph Convolutional NetworksPart 2: Semi-Supervised Learning with Spectral Graph ConvolutionsTobias Skovgaard JepsenBlockedUnblockFollowFollowingJan…

Continue Reading## Practical NumPy — Understanding Python library through its functions

Practical NumPy — Understanding Python library through its functionsKillol GovaniBlockedUnblockFollowFollowingJan 10Before embarking on the journey of data science and machine learning, it…

Continue Reading## Singular Value Decomposition with Example in R

Let’s see. When we decompose our matrix A into U, D, V then a few left-most columns of all three…

Continue Reading## Baffled by Covariance and Correlation??? Get the Math and the Application in Analytics for both the terms..

The values from PCA done using the correlation matrix are closer to each other and more uniform as compared to…

Continue Reading## Srishti Saha

Let us understand the correlation matrix and covariance matrixCovariance and correlation are two…Data Preparation and Preprocessing is just as important creating…

Continue Reading## Convolutional Neural Network

ANN Calculation for each layerwhere,x — is the input vector with dimension [p_l, 1]W — Is the weight matrix with dimensions [p_l, n_l] where, p_l…

Continue Reading## The Mathematics Behind Principal Component Analysis

The whole process of obtaining principle components from a raw dataset can be simplified in six parts :Take the whole dataset…

Continue Reading## Demystifying ‘Confusion Matrix’ Confusion

Then you may consider additional metrics like Precision, Recall, F score (combined metric), but before diving in lets take a…

Continue Reading## Change of Basis

He arrives at the similarity transformation 11 minutes into the video.Ok, now that we all agree the change of basis…

Continue Reading## Earth coordinate system

To understand how to visualize the data we get from the device sensors, look at the image below.Form Android DevelopersWhen…

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