Category: PyTorch

In this part of the Deep Learning series, we will introduce the concept of the Sequence-to-Sequence (also known as the Encoder-Decoder) model in the context of a Language Translation use-case. In addition, we will get our hands dirty to demonstrate the translation of English sentences to Spanish sentences. To accomplish this task, we will implement an GRU model using PyTorch.

Here is the link to the article on Deep Learning demonstrating the English-to-Spanish Language Translation using GRU:

Deep Learning – Sequence-to-Sequence Model

Enjoy 🙂 !!!

In this part of the Deep Learning series, we will explain how a Gated Recurrent Unit (GRU) network works and use PyTorch for a practical demonstration to predict the Next Word.

Here is the link to the article on Deep Learning using GRU:

Deep Learning – Gated Recurrent Unit

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In this part of the Deep Learning series, we will get our hands dirty to demonstrate the prediction of the ‘Next Word’, given an input sequence of two words from a text corpus. To accomplish this task, we will implement an LSTM model using PyTorch.

Here is the link to the article on Deep Learning demonstrating the ‘next word’ prediction using LSTM:

Deep Learning – Predict Next Word Using LSTM

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In this part of the Deep Learning series, we will explain how a Bidirectional Recurrent Neural Network (RNN) works and use PyTorch for a practical demonstration of Bidirectional RNN to predict the Sentiments of the Restaurant Reviews.

Here is the link to the article on Deep Learning using Bidirectional RNN:

Deep Learning – Bidirectional Recurrent Neural Network

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In this part of the Deep Learning series, we will explain how a Long Short Term Memory (LSTM) network works and use PyTorch for a practical demonstration of LSTM to predict the Sentiments of the Restaurant Reviews.

Here is the link to the article on Deep Learning using LSTM:

Deep Learning – Long Short Term Memory

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In this part of the Deep Learning series, we will explain how a Recurrent Neural Network (RNN) works and use PyTorch for a practical demonstration of RNN to predict the Sentiments of the Restaurant Reviews.

Here is the link to the article on Deep Learning using RNN:

Deep Learning – Recurrent Neural Network

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In Part-7 of the Deep Learning series, we will end the journey on the popular open source Deep Learning framework called PyTorch. In this part of the article, we will cover the following topics:

• • Datasets and DataLoaders
  • Multi-class Classification
  • Saving and Loading a Model

Here is the link to the Part-7 article on Deep Learning:

Introduction to Deep Learning – Part 7

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In Part-6 of the Deep Learning series, we will continue our journey with the popular open source Deep Learning framework called PyTorch. In this part of the article, we will create, train, and evaluate a Non-Linear model.

Here is the link to the Part-6 article on Deep Learning:

Introduction to Deep Learning – Part 6

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In Part-5 of the Deep Learning series, we will continue our journey with the popular open source Deep Learning framework called PyTorch to create our first Linear model.

Here is the link to the Part-5 article on Deep Learning:

Introduction to Deep Learning – Part 5

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In Part-4 of the Deep Learning series, we will start to get our hands dirty with the popular open source Deep Learning framework called PyTorch.

Here is the link to the Part-4 article on Deep Learning:

Introduction to Deep Learning – Part 4

Enjoy 🙂 !!!