Tag deep learning

Hi there, and welcome to my blog.

Here you'll find resources about data science, software engineering, and life. Well, maybe not life...

Hope you enjoy.

Get updated of new posts

The accessibility of GPT-2 - text generation and fine-tuning

Text generation using GPT-2 is quite easy, using the right tools. Learn how to do it, as well as how to fine-tune the model on your own dataset.

There are comments.

Mixture of Variational Autoencoders - a Fusion Between MoE and VAE

An unsupervised approach to digit classification and generation.

There are comments.

Preparing for the Unexpected

How to apply your model to input it has never seen before.

There are comments.

Think your Data Different

Learn how node2vec works, and what kind of information it captures that word2vec doesn’t — includes case study.

There are comments.

Variational Autoencoders Explained in Detail

Learn all the details needed to implement a variational autoencoder, code included.

There are comments.

How to Engineer Your Way Out of Slow Models

So you just finished designing that great neural network architecture. But how do you handle the fact it is slow?

There are comments.

Zooming Past the Competition

How to create an Augmented Reality app that allows a user to get content recommendations.

There are comments.

Variational Autoencoders Explained

Ever wondered how the Variational Autoencoder model works? Keep reading to find out.

There are comments.

Uncertainty for CTR Prediction: One Model to Clarify Them All

Learn how to handle uncertainty in recommender systems in a principled way using one unified model.

There are comments.

Recommender Systems: Exploring the Unknown Using Uncertainty

Learn what the exploration-exploitation tradeoff is, and how to use your model's uncertainty to explore new items in a wise manner.

There are comments.

Page 1 / 2