Neural Network Embeddings Explained

How deep learning can represent War and Peace as a vector

Easy to read #novice article about #embeddings. Basically — how to represent everything as a vector.

Link: https://towardsdatascience.com/neural-network-embeddings-explained-4d028e6f0526

Dynamic Meta-Embeddings for Improved Sentence Representations

While one of the first steps in many NLP systems is selecting what pre-trained word embeddings to use, we argue that such a step is better left for neural networks to figure out by themselves. To that end, we introduce dynamic meta-embeddings, a simple yet effective method for the supervised learning of embedding ensembles, which leads to state-of-the-art performance within the same model class on a variety of tasks. We subsequently show how the technique can be used to shed new light on the usage of word embeddings in NLP systems.

Paper: https://research.fb.com/wp-content/uploads/2018/10/Dynamic-Meta-Embeddings-for-Improved-Sentence-Representations.pdf
Link: https://research.fb.com/publications/dynamic-meta-embeddings-for-improved-sentence-representations/

P.S. Note the date of the publication

#embeddings #NLP #facebook

Amazon’s SageMaker Object2Vec, a highly customizable algorithm that can learn embeddings of various types high-dimensional objects.

Link: https://aws.amazon.com/ru/blogs/machine-learning/introduction-to-amazon-sagemaker-object2vec/

#Object2Vec #Amazon #Embeddings

​​Open-sourcing PyTorch-BigGraph for faster embeddings of extremely large graphs

PyTorch-BigGraph— a tool that for faster and easier producing graph embeddings for extremely large graphs. Outputs high-quality embeddings without specialized computing resources like GPUs or huge amounts of memory.

Link: https://ai.facebook.com/blog/open-sourcing-pytorch-biggraph-for-faster-embeddings-of-extremely-large-graphs/
Github: https://github.com/facebookresearch/PyTorch-BigGraph

#PyTorch #Facebook #OpenSourceRelease #Embeddings #GraphLearning

Learning a unified embeding for visual search at #Pinterest

How Pinterest created unified embeddings for images from different fields searching instead three different by use #multitask approach.

Link: https://blog.acolyer.org/2019/10/11/learning-a-unified-embedding-for-visual-search-at-pinterest/

#Search #CV #embeddings

​​Supporting content decision makers with machine learning

#Netflix shared a post providing information about how they research and prepare data for new title production.

Link: https://netflixtechblog.com/supporting-content-decision-makers-with-machine-learning-995b7b76006f

#NLU #NLP #recommendation #embeddings

🦜 Hi!

We are the first Telegram Data Science channel.

Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.


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