- The Rise of Vector Data - May 25, 2021.
Embedding models convert raw data such as text, images, audio, logs, and videos into vector embeddings (“vectors”) to be used for predictions, comparisons, and other cognitive-like functions.
Distributed Representation, Pinecone, Representation
- Graph Representation Learning: The Free eBook - Jan 19, 2021.
This free eBook can show you what you need to know to leverage graph representation in data science, machine learning, and neural network models.
Data Science, Free ebook, Graph, Neural Networks, Representation
- Disentangling disentanglement: Ideas from NeurIPS 2019 - Jan 15, 2020.
This year’s NEURIPS-2019 Vancouver conference recently concluded and featured a dozen papers on disentanglement in deep learning. What is this idea and why is it so interesting in machine learning? This summary of these papers will give you initial insight in disentanglement as well as ideas on what you can explore next.
AI, Deep Learning, Disentanglement, NeurIPS, Representation, Research
- Text Encoding: A Review - Nov 22, 2019.
We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.
Data Preprocessing, NLP, Representation, Rosaria Silipo, Text Analytics, Word Embeddings
A “Weird” Introduction to Deep Learning - Mar 30, 2018.
There are amazing introductions, courses and blog posts on Deep Learning. But this is a different kind of introduction.
Pages: 1 2
Deep Learning, Dropout, Neural Networks, Representation, Tensor, TensorFlow
