Introduction to Seq2Seq Translators with PyTorch
Neural Machine Translation is the practice of using Deep Learning to generate an accurate translation of text from one language to another.
3 years ago
Articles
Understanding Facial Recognition with Deep Learning
In this new tutorial, you will learn how to harness dlib to recognize faces in your personal photos.
3 years ago
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NLP
GPT-NeoX: A 20 Billion Parameter NLP Model on Gradient Multi-GPU
Follow this guide to learn how to set up and use GPT-NeoX-20B within Paperspace Gradient to generate text in response to an inputted prompt.
By
Nick Ball
Developing a Tic Tac Toe Gaming Agent with Genetic Algorithms: Putting it all together (Part 3)
In the conclusion to the tutorial series on solving tic tac toe with the genetic algorithm, you will put all the lessons together to apply them to the game itself.
3 years ago
Object Localization using PyTorch, Part 2
Follow part 2 of this tutorial series to see how to train a classification model for object localization using CNN's and PyTorch. Then see how to save and convert the model to ONNX.
3 years ago
Object Localization using PyTorch, Part 1
In part one of this series on object localization with pytorch, you will learn the theory behind object localization, and learn how to set up the dataset for the task.
3 years ago
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Notebooks
Now available: Run JAX on Gradient Notebooks
Follow this guide to learn about the JAX library, and learn how to directly implement it in Gradient.
3 years ago
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Machine Learning
Weights & Biases with Gradient
Follow this guide to learn how to integrate the Weights and Biases API with your code in Gradient Notebooks! Readers should expect to learn how to get started with Weights and Biases, how to integrate it with Gradient, and how to log your training results in Weights and Biases via Gradient.
3 years ago
A primer to Interpretable Machine Learning
This tutorial seeks to eliminate much of the difficulties that come with data storytelling in the world of Machine Learning. Readers can expect to finish the article with an understanding of how to use the available tools in Python to create interpretable ML projects on platforms like Gradient.
3 years ago
