Recognising Songs of Endangered Bird Species from Kerala using Deep Learning Techniques

Leave a Comment / Conceptual /

Overview Birds are an incredibly diverse group of animals found all over the Earth. With over 10,000 known species, they come in all shapes, sizes, and colours, and they play a vital role in maintaining the delicate balance of ecosystems around the world. One of the most important roles that birds play is that of […]

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decision tree

Decision Tree: A Machine Learning Algorithm

Leave a Comment / Machine Learning Fundamentals /

Decision tree is a non-parametric supervised machine learning algorithm which makes use of a tree like structure to make decisions. Decision tree algorithms can be used for both classification and regression though it is mostly meant for classification tasks. Decision trees consist of three types of nodes such as root node, leaf nodes and decision

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Essential Molecular Biology for Bioinformaticians

Leave a Comment / Computational Biology, Conceptual /

As a bioinformatician, you will be working with large amounts of biological and molecular data, which means that you need to have a solid understanding of the fundamental concepts in these fields. Molecular biology is a fascinating and complex field of study that deals with the study of the biological processes at the molecular level.

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Machine learning Interview Questions (Part-7)

Leave a Comment / ML Interview Questions /

This is another addition to the series of machine learning (ML) interview questions and answers that have been published on this website. What are Sigmoid function and softmax functions? Explain the difference Sigmoid and softmax functions are functions used for the classification tasks in machine learning and deep learning. Both Sigmoid function and softmax function

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Logistic Regression for Classification in Machine Learning

1 Comment / Conceptual, Tutorial /

Logistic regression is an analytical technique in supervised machine learning for performing classification tasks. It is a classification algorithm based on probabilistic approach. Logistic regression approach can be used to make predictions on a categorical dependent variable. The algorithm extracts inferences from a given set of independent input variables and these inferences are used to

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