Conceptual

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

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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Essential Molecular Biology for Bioinformaticians

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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Emotional Intelligence: A trait to success

Emotional intelligence can be understood as an ability to know our own emotions and being able to handle it in the best ways. Studies revealed intelligent quotients contribute 20 % of success in our life whereas 80% comes from our emotional intelligence. Emotional intelligence helps people to stay calm and hopeful when a difficult situation …

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Logistic Regression for Classification in Machine Learning

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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Hyperparameters in Machine Learning

Introduction Hyperparameters are the parameters that are explicitly defined by the user for the machine learning model. This helps the learning process of the machine learning algorithm. The prefix “hyper” in hyperparameter means top-level, indicating these are the controlling parameters to ensure model performance. The user selects the value of the hyperparameter before the training …

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