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Articles by Mithilesh Pradhan
Page 4 of 5
Role of Log Odds in Logistic Regression
Introduction Logistic Regression is a statistical method to predict a dependent data variable based on the relationship between one or more independent variables. It makes use of log odds and with the help of a logistic function, it predicts the probability of an event occurring. It is a classification method. What are Log Odds and Why are they Useful for Logistic Regression? Logistic regression is used to predict binary outcomes. For example, in an election, whether a candidate will win or not, whether SMS is spam or ham, etc. Odds are the ratio of the probability of success to failure. ...
Read MoreLocally Weighted Linear Regression in Python
Locally Weighted Linear Regression is a non−parametric method/algorithm. In Linear regression, the data should be distributed linearly whereas Locally Weighted Regression is suitable for non−linearly distributed data. Generally, in Locally Weighted Regression, points closer to the query point are given more weightage than points away from it. Parametric and Non-Parametric Models Parametric Parametric models are those which simplify the function to a known form. It has a collection of parameters that summarize the data through these parameters. These parameters are fixed in number, which means that the model already knows about these parameters and they do not depend on the ...
Read MoreImplementation of Whale Optimization Algorithm
Introduction Whale Optimization Algorithm is a technique for solving optimization problems in Mathematics and Machine Learning. It is based on the behavior of humpback whales which uses operators like prey searching, encircling the prey, and forging bubble net behavior of humpback whales in the ocean. It was given by Mirjalili and Lewis in 2016. In this article, we are going to look into the different phases of the WOA algorithm A History of Humpback Whales Humpback whales are one of the largest mammals on Earth. They have a special type of hunting mechanism known as the bubble−net hunting mechanism. They ...
Read MoreImage Recognition using MobileNet
Introduction The process of identifying an object or feature with an image is known as Image Recognition. Image recognition finds its place in diverse domains be it Medical imaging, automobiles, security, or detecting defects. What is MobileNet and Why is it so Popular? MobileNet is deep learning CNN model developed using depth−wise separable convolutions. This model highly decreases the number of parameters when compared to other models of the same depth. This model is lightweight and is optimized to run on mobile and edge devices. There are three versions of Mobilenet released so far.ie MobileNet v1, v2 and v3. Mobilenet ...
Read MoreHow to Improve UX With Machine Learning?
Introduction User experience (UX) is how a person or user interacts with a product, service, or system encompassing everything from ease of usage, and its usefulness to efficiency. Today, Machine Learning can provide an intuitive user experience through modeling, customization, clustering, and segregation. In this article, let's have a look at how Machine Learning is revolutionizing User Experience. Why does User Experience Matters? In the case of a business that needs to attract customers or to make sales via a website or mobile app UX is almost needed. The duration of time the user spends on these platforms, their search ...
Read MoreTraining vs Testing vs Validation Sets
In this article, we are going to learn about the difference between – Training, Testing, and Validation sets Introduction Data splitting is one of the simplest preprocessing techniques we can use in a Machine Learning/Deep Learning task. The original dataset is split into subsets like training, test, and validation sets. One of the prime reasons this is done is to tackle the problem of overfitting. However, there are other benefits as well. Let's have a brief understanding of these terms and see how they are useful. Training Set The training set is used to fit or train the model. These ...
Read MoreTop 7 Artificial Intelligence and Machine Learning Trends For 2022
In this article, let’s explore 7 such areas which are promising and booming in 2022 related to Artificial Intelligence. Introduction Over the last decade, we saw tremendous growth and development in Artificial Intelligence-related technologies in almost every domain and is still becoming more relevant in the current era or decade. There have been ground-breaking research in AI and ML which has changed the current scenario of how we pursue technology infused with machine intelligence.AI related technology has found application in every domain. To name a few like Healthcare, Cybersecurity, HR Processes, Space exploration, and many more. Trends in 2022 1. ...
Read MoreRegression Analysis and the Best Fitting Line using C++
Introduction Regression Analysis is the most basic form of predictive analysis. In Statistics, linear regression is the approach of modeling the relationship between a scalar value and one or more explanatory variables. In Machine learning, Linear Regression is a supervised algorithm. Such an algorithm predicts a target value based on independent variables. More About Linear Regression and Regression Analysis In Linear Regression / Analysis the target is a real or continuous value like salary, BMI, etc. It is generally used to predict the relationship between a dependent and a bunch of independent variables. These models generally fit a linear equation, ...
Read MoreRegression Analysis and the Best Fitting Line using Python
In this tutorial, we are going to implement regression analysis and the best-fitting line using Python programming Introduction Regression Analysis is the most basic form of predictive analysis. In Statistics, linear regression is the approach of modeling the relationship between a scalar value and one or more explanatory variables. In Machine learning, Linear Regression is a supervised algorithm. Such an algorithm predicts a target value based on independent variables. More About Linear Regression and Regression Analysis In Linear Regression / Analysis the target is a real or continuous value like salary, BMI, etc. It is generally used to predict the ...
Read MoreMulticlass image classification using Transfer learning
Introduction One of the most common tasks involved in Deep Learning based on Image data is Image Classification. Image classification has become more interesting in the research field due to the development of new and high-performing machine learning frameworks. Such classification can either be binary where two classes of images are present or multiclass classification which deals with more than two image classes. Here, in this article, we are going to explore transfer learning with multiclass image classification. Multiclass Image Classification With the advancement in artificial Neural networks and the development of Convolutional Neural Networks complex operations on images have ...
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