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Feb 5, 2021

Steps in Building a Machine Learning Project

In this post, we will be discussing the basic steps in building a machine learning project. The process of building an ML project includes collecting the dataset, cleaning it, processing the data, training and testing of the model and deploying it. All the steps are explained briefly below. Data collection Data collection…

Machine Learning

2 min read


Feb 5, 2021

any() and all() in Python

In this post, we will be looking into any() and all() functions in Python. First, let us discuss the any() function. 👉 any() The any() function takes an iterable as an argument: any(iterable). The iterable can be a list, tuple or dictionary. The any() function returns ‘True’ if any element in the…

Python

2 min read


Feb 5, 2021

What is Logistic Regression

As you may be knowing Logistic Regression is a Machine Learning algorithm. It is used for binary classification problems. We also have multiclass logistic regression, where we basically re-run the binary classification multiple times. It is a linear algorithm with a non-linear transform at the output. The input values are…

Machine Learning

3 min read

What is Logistic Regression
What is Logistic Regression

Feb 5, 2021

Padding in CNN

We have seen the basic operation of convolution in the previous post. Knowing Convolution Basics In this post, we will be discussing padding in Convolutional Neural Networks. Padding is the number of pixels that are added to an input image. …

Convolution Neural Net

2 min read

Padding in CNN
Padding in CNN

Published in Analytics Vidhya

·Feb 5, 2021

Knowing Convolution Basics

In this article, we are going to learn about the grayscale image, colour image and the process of convolution. Grayscale image A grayscale image where the image is represented as only the shades of grey. The intensity of the various pixels of the image is denoted using the values from 0 to…

Image Processing

4 min read

Knowing Convolution Basics
Knowing Convolution Basics

Feb 5, 2021

What is Gradient descent algorithm?

The gradient descent algorithm is an approach to find the minimum point or optimal solution for a given dataset. It follows the steepest descent approach. That is it moves in the negative gradient direction to find the local or global minima, starting out from a random point. …

Machine Learning

3 min read

What is Gradient descent algorithm?
What is Gradient descent algorithm?

Feb 5, 2021

Confusion Matrix

Today we are going to discuss some of the metrics in classification. Let us first look at the confusion matrix. The Accuracy is calculated as:-

Confusion Matrix

3 min read

Confusion Matrix
Confusion Matrix

Jun 1, 2020

Population and Sample

Today let’s look at the topic population and sample. Population refers to the collection of all the elements in a dataset. It is usually a large number and hence the processing of data of the whole population is a tedious task. Population data is hard to observe and to deal…

Statistics

2 min read

Population and Sample
Population and Sample

May 30, 2020

Gaussian Distribution

It is a type of continuous probability distribution for a random variable. It is also called as Normal distribution. The general form of its probability density function is; Here the parameter µ is the mean or expectation of the distribution and σ is the standard deviation. When the mean becomes…

Gaussian Distribution

2 min read

Gaussian Distribution
Gaussian Distribution

May 27, 2020

Knowing Probability Distributions…

A probability distribution is a function that describes the chances of finding a random variable over a defined range. Below is the list of some of the most used probability distribution functions. Normal(Gaussian) distribution. Log-Normal distribution. Bernoulli distribution. Binomial distribution. Poisson distribution. Today let’s see what are Bernoulli, Binomial and…

Probability

2 min read

Knowing Probability Distributions…
Knowing Probability Distributions…
Ashwin Sharma P

Ashwin Sharma P

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