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Deep Learning Neural Network

Neural Network: A Complete Beginners Guide in 2019

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Classification

Linear Classifiers: An Introduction to Classification

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Regression

Multiple Regression from Scratch in Python

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Regression

Simple Linear Regression: An Introduction to Regression from scratch

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Deep Learning

Bias-Variance: A Comprehensive Graphical Representation

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Neural Network: A Complete Beginners Guide in 2019

in Deep Learning Neural Network on August 21, 2019 September 1, 2019 Share Facebook Twitter Pinterest Google+ Email 0

Neural Network has become a crucial part of modern technology. It has influenced our daily life in a way that we have never imagined. From e-commerce and solving classification problems to autonomous driving, it has…

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Linear Classifiers: An Introduction to Classification

in Classification on August 15, 2019 August 15, 2019 Share Facebook Twitter Pinterest Google+ Email 2

Linear Classifiers are one of the most commonly used classifiers and Logistic Regression is one of the most commonly used linear classifiers. The concepts we are going to learn here will actually extend a lot…

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Multiple Regression from Scratch in Python

in Regression on July 20, 2019 September 9, 2019 Share Facebook Twitter Pinterest Google+ Email 2

Previously, we have discussed briefly the simple linear regression. Here we will discuss multiple regression or multivariable regression and how to get the solution of the multivariable regression. At the end of the post, we…

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Simple Linear Regression: An Introduction to Regression from scratch

in Regression on July 13, 2019 August 15, 2019 Share Facebook Twitter Pinterest Google+ Email 1

Regression is a very fundamental concept in statistics, machine learning and in Neural Network. Imagine plotting the correlation between rainfall frequency and agriculture production in high school. Increase in rainfall generally increases agriculture production. Fitting…

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Bias-Variance: A Comprehensive Graphical Representation

in Deep Learning on June 18, 2019 October 30, 2019 Share Facebook Twitter Pinterest Google+ Email 1

To build an accurate machine learning model we need to have a proper understanding of the error. In forming predictions of a model there are three sources of error: noise, bias, and variance. Having proper…

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Differential Equations: Classification

in Differential Equations on April 20, 2019 July 15, 2019 Share Facebook Twitter Pinterest Google+ Email 0

Differential Equations An equation involving derivatives of one or more dependent variables with respect to one or more independent variables is called a differential equation. For example: \begin{equation} \frac{d^{2}y}{dx^2} + xy \left( \frac{dy}{dx}\right)^2 = 0…

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IRIS Data Classification Using Neural Net

in Neural Network on March 31, 2019 June 2, 2019 Share Facebook Twitter Pinterest Google+ Email 0

The Iris flowers dataset is one of the best-known datasets found in the classification literature. The goal is to classify Iris flowers among three species (Setosa, Versicolor or Virginica) from measurements of length and width…

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Mac address

An Overview of MAC Addresses

in Networking on March 29, 2019 June 2, 2019 Share Facebook Twitter Pinterest Google+ Email 1

History In 1983, computer networking was totally different than it is today. One of the notable differences in land topology was that switchable hub hadn’t been invented yet. This meant that frequently, many or all…

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Categories

  • Classification (1)
  • Deep Learning (2)
  • Differential Equations (1)
  • Networking (1)
  • Neural Network (2)
  • Regression (2)

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Deep Learning (1) multiple regression (1) regresssion (2) simple linear regression (1)