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Understanding Loss Function in Deep Learning

Analytics Vidhya

Introduction The loss function is very important in machine learning or deep learning. let’s say you are working on any problem and you have trained a machine learning model on the dataset and are ready to put it in front of your client. […].

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Brief Introduction to Tensorflow for Deep Learning

Analytics Vidhya

Source: Reference 1 Introduction Tensorflow is a popular open-source machine learning framework developed by Google. It is primarily used by machine learning practitioners in research and industry for the training and inference of deep neural networks.

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Analyzing and Comparing Deep Learning Models

Analytics Vidhya

Deep Learning Overview Deep Learning is a subset of Machine Learning. Deep Learning is established on Artificial Neural Networks to mimic the human brain. In deep learning, we add several hidden layers to gather the most minute details to learn the data for […].

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A Basic Introduction to Tensorflow in Deep Learning

Analytics Vidhya

Introduction The Tensorflow framework is an open end-to-end machine learning platform. It’s a symbolic math toolkit that integrates data flow and differentiable programming to handle various tasks related to deep neural network training and inference.

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Advance Guide on Interview Questions of Deep Learning

Analytics Vidhya

Introduction Deep learning is a branch of machine learning inspired by the brain’s ability to learn. It is a data-driven approach to learning that can automatically extract features from data and build models to make predictions. Deep learning has revolutionized many areas of […].

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Machine Learning with Limited Data

Analytics Vidhya

Introduction In machine learning, the data’s amount and quality are necessary to model training and performance. The amount of data affects machine learning and deep learning algorithms a lot. The post Machine Learning with Limited Data appeared first on Analytics Vidhya.

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Image Classification Using Resnet-50 Deep Learning Model

Analytics Vidhya

Introduction In this article, we will train a classification model which uses the feature extraction + classification principle, i.e., firstly, we extract relevant features from an image and then use these feature vectors in machine learning classifiers to perform the final classification. We will […].