How to run a basic RNN model using Pytorch?

How to run a basic RNN model using Pytorch?

How to run a basic RNN model using Pytorch?

This Pytorch recipe inputs a dataset into a basic RNN (recurrent neural net) model and makes image classification predictions.


This recipe uses the MNIST handwritten digits dataset for image classification. The RNN model predicts what the handwritten digit is. The recipe uses the following steps to accurately predict the handwritten digits:
- Import Libraries
- Prepare Dataset
- Create RNN Model
- Instantiate Model Class
- Instantiate Loss Class
- Instantiate Optimizer Class
- Tran the Model
- Prediction

This recipe uses the helpful PyTorch utility DataLoader - which provide the ability to batch, shuffle and load the data in parallel using multiprocessing workers.

What is RNN ?
A recurrent neural network (RNN) is a type of deep learning artificial neural network commonly used in speech recognition and natural language processing (NLP). This neural net processes sequential data, and takes in as input both the new input and the output (or a hidden layer) of the net in the previous step. Since they have backward connection in their hidden layers they have memory states.

What is PyTorch ?
Pytorch is a Python deep learning library that uses the power of graphics processing units. Its strengths compared to other tools like tensorflow are its flexibility and speed. You can use other Python packages such as NumPy, SciPy to extend PyTorch functionalities.

Relevant Projects

Predict Credit Default | Give Me Some Credit Kaggle
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.

Predict Employee Computer Access Needs in Python
Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

Customer Market Basket Analysis using Apriori and Fpgrowth algorithms
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.

Sequence Classification with LSTM RNN in Python with Keras
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset​ using Keras in Python.

Mercari Price Suggestion Challenge Data Science Project
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.

PySpark Tutorial - Learn to use Apache Spark with Python
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.

Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

Data Science Project-TalkingData AdTracking Fraud Detection
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.

Predict Macro Economic Trends using Kaggle Financial Dataset
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.

German Credit Dataset Analysis to Classify Loan Applications
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.