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Deep Learning Tutorial
Last Updated: 09 May 2023
Deep learning is a branch of machine learning which is completely based on artificial neural networks, as neural networks are going to mimic...read more
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Convolutional Neural Network (CNN) in Machine Learning
Last Updated: 13 March 2024
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What is Adam Optimizer?
Last Updated: 20 March 2024
Prerequisites :  Optimization techniques in Gradient DescentAdam Optimizer Adaptive Moment Estimation is an algorithm for optimization tec...read more
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Self - attention in NLP
Last Updated: 10 January 2024
Self-attention was proposed by researchers at Google Research and Google Brain. It was proposed due to challenges faced by the encoder-decod...read more
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Image Caption Generator using Deep Learning on Flickr8K dataset
Last Updated: 02 September 2020
Generating a caption for a given image is a challenging problem in the deep learning domain. In this article, we will use different techniqu...read more
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Residual Networks (ResNet) - Deep Learning
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After the first CNN-based architecture (AlexNet) that win the ImageNet 2012 competition, Every subsequent winning architecture uses more lay...read more
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Explanation of BERT Model - NLP
Last Updated: 10 January 2024
BERT, an acronym for Bidirectional Encoder Representations from Transformers, stands as an open-source machine learning framework designed f...read more
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CNN | Introduction to Pooling Layer
Last Updated: 21 April 2023
The pooling operation involves sliding a two-dimensional filter over each channel of feature map and summarising the features lying within t...read more
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Deep Q-Learning
Last Updated: 23 January 2023
Q-Learning is required as a pre-requisite as it is a process of Q-Learning creates an exact matrix for the working agent which it can "refer...read more
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ML | Stochastic Gradient Descent (SGD)
Last Updated: 14 March 2024
Gradient Descent is an iterative optimization process that searches for an objective function's optimum value (Minimum/Maximum). It is one o...read more
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Think about how a machine learns from the data in machine learning and deep learning during training.  This involves a large amount of data...read more
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Last Updated: 08 December 2023
Long Short-Term Memory is an improved version of recurrent neural network designed by Hochreiter Schmidhuber. LSTM is well-suited for seque...read more
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Generative Adversarial Network (GAN)
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GAN(Generative Adversarial Network) represents a cutting-edge approach to generative modeling within deep learning, often leveraging archite...read more
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seq2seq Model in Machine Learning
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Seq2Seq model or Sequence-to-Sequence model, is a machine learning architecture designed for tasks involving sequential data. It takes an in...read more
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Deep learning is a branch of machine learning which is based on artificial neural networks. It is capable of learning complex patterns and r...read more
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