#machinelearning

All You Need To Know About Decision Tree Algorithm

Reading Time: 5 minutes In this blog, we are going to discuss Decision Tree algorithm, a supervised algorithm which can be used to solve both regression and as well as classification problem too. A classification algorithm, in general, is a function that weighs the input features so that the output separates one class into positive values and the other into negative values. Introduction to Decision Tree Algorithm A decision tree Continue Reading

Music Genre Classification: Identification Of The Audio

Reading Time: 4 minutes In this blog, we will discuss and build a music genre classification model to predict the genre/label of the music/song. Music Genre Classification Today we will build a Tensorflow sequential model to automatically classify different musical genres from the given input audio files. Dataset To train our ml classifier model to predict the audio’s genre/label, we will use the GTZAN Dataset.You can download the dataset Continue Reading

Explore OpenCV & Why Do We Need To Know About It?

Reading Time: 4 minutes OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. OpenCV OpenCV is the huge open-source library for computer vision, Continue Reading

Explore how to apply continual learning to your machine learning models

Reading Time: 3 minutes In this blog, we will be learning about continual learning (CI) importance in artificial intelligence. Continual Learning means the ability of a model to learn independently whenever new data comes in. Some may know it as auto-adaptive learning, or continual AutoML. The idea of CL is to mimic human’s ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. For example, we’ve Continue Reading

How Feature selection techniques for machine learning are important?

Reading Time: 5 minutes Feature selection is a way of selecting the subset of the most relevant features from the original features set by removing the redundant, irrelevant, or noisy features. Features are the input variables that we provide to our models. Each column in our dataset constitutes a feature. To train an optimal model, we need to make sure that we use only the essential features. If we Continue Reading