How to leverage a powerful pre-trained convolution neural network to extract embedding vectors for pictures. — In this tutorial, I will show you how to leverage a powerful pre-trained convolution neural network to extract embedding vectors that can accurately describe any kind of picture in an abstract latent feature space. I will show some examples of using ResNext-WSL on the COCO dataset using the library PyTorch and…

How to take a collection of vector embeddings and average them preserving the multi-sense topicality of their manifold structures. — This is the third article of the “Embed, Cluster, and Average” series. Before diving deep into this tutorial, I recommend reading first the previous two articles: Extracting rich embedding features from pictures using PyTorch and ResNeXt-WSL and Manifold clustering in the embedding space using UMAP and GMM.

How to reduce the dimensionality of embedding vectors and preserving manifold structures grouped into clusters. — In the previous article Extracting rich embedding features from pictures using PyTorch and ResNeXt-WSL we have seen how to represent pictures into a multi-dimensional numerical embedding space. We have also seen the effectiveness of the embedding space to represent similar pictures closely to each other. In this tutorial, we will…

Over the last decade, I have worked with highly talented data science teams from several different industries, including marketing, advertising, automotive, financial services, and cybersecurity. I have contributed to most of the lifecycle phases, worked with executives and stakeholders across many different functions, and seen recent advancements in the machine…

This piece is part of a series on 2019 trends in the AI and Machine Learning industry. You can read my full thoughts on the past year in this summary I wrote for the Helixa blog, which also includes links to the other in-depth pieces in this series. Symbolic AI…

This piece is part of a series on 2019 trends in the AI and Machine Learning industry. You can read my full thoughts on the past year in — — this summary I wrote for the Helixa blog, which also includes links to the other in-depth pieces in this series. …

This piece is part of a series on 2019 trends in the AI and Machine Learning industry. You can read my full thoughts on the past year in this summary I wrote for the Helixa blog, which also includes links to the other in-depth pieces in this series. There is…

This piece is part of a series on 2019 trends in the AI and Machine Learning industry. You can read my full thoughts on the past year in this summary I wrote for the Helixa blog, which also includes links to the other in-depth pieces in this series. “Federated Learning”…

This piece is part of a series on 2019 trends in the AI and Machine Learning industry. You can read my full thoughts on the past year in this summary I wrote for the Helixa blog, which also includes links to the other in-depth pieces in this series. 2019 was…