Tutorials

Understanding Attention mechanism and Machine Translation Using Attention-Based LSTM (Long Short...

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First, let us understand why an Attention Mechanism made machine translation easy. Previously encoder-decoder models were used for machine translation. The encoder-decoder model contains...

Gradient Descent Optimization Technique In Machine learning

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Optimization in machine learning is the process of updating weights and biases in the model to minimize the model's overall loss. While backpropagating in...

Logistic Regression with Keras

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This article explains what Logistic Regression is, its intuition, and how we can use Keras layers to implement it. What is Logistic Regression? It is a...

Introduction to Recurrent Neural Networks

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In typical neural networks, all the inputs and outputs are independent of each other, Which means each hidden layer has its separate set of...

Image Data Augmentation in Keras

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When dealing with Deep Learning on images, the first question that arises in your mind is where you will get this particular type of...

Transfer Learning in Keras (Image Recognition)

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Transfer Learning in AI is a method where a model is developed for a specific task, which is used as the initial steps for...

Generating Your Shakespeare Text Using Sequential Models Such As Long-Short-Term-Memory (LSTMs),...

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In the previous article, we discussed Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) and applied them to detect fake news. This article will...

Introduction to Support Vector Machines (SVMs)

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Support Vector Machines (SVMs) are supervised learning models for classification and regression problems. Support Vector Machines(SVMs) are supervised learning models for classification and regression...

Fake News Detection Using Word Embeddings, Artificial Neural Networks, and Convolutional...

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In this article, we will learn how to use Deep Learning models for NLP. Since the model takes numerical vectors as input, we need...

Optimizing Hyperparameters Using The Keras Tuner Framework

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Hyperparameter optimization is an integral part of deep learning as a machine learning project is crucially dependent on the choice of good hyperparameters. Neural...