Vishnuprasanth Vijaya Kumar

Sr. Data Scientist @ Cigna || Lead MLE @ Omdena || Data Scientist Intern @ Viviana Luxury and MTE|| Writer || Ferroequinologist

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Real-world applications of machine learning and challenges in ML implementation

There are a variety of real-world applications of machine learning, including predictive analytics, computer vision, and more....

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Machine Learning

Evaluating machine learning models-metrics and techniques

Evaluation metrics provide objective criteria to measure predictive ability, generalization capability, and overall quality of models....

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Machine Learning

Demystifying machine learning 101: A comprehensive overview

We will demystify the concept and provide a comprehensive overview of machine learning....

Supervised vs. unsupervised learning 101: Key differences and applications

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Machine Learning

Supervised vs. unsupervised learning 101: Key differences and applications

We will explore the concepts of supervised and unsupervised learning and highlight their key differences....

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Understanding the bias-variance tradeoff in machine learning

Whenever we speak about model prediction, it is essential to comprehend prediction errors (bias and variance). There is a tradeoff between a model’...

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Machine Learning

Boosting and bagging: Powerful ensemble methods in machine learning

While working on a classification problem, a regression analysis, or another data science project, bagging, and boosting algorithms can play a vital role....

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Machine Learning

Choosing the right machine learning algorithm for your problem

This blog will try to break down how to select a machine learning algorithm from a practical approach....

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Machine Learning

The power of feature engineering for machine learning success

Feature engineering consists of the selection, manipulation, and transformation of raw data into features used in supervised learning....