Attention mechanism in Deep Learning, Explained

Time Series Forecasting with Deep Learning and Attention Mechanism

An overview of the architecture and the implementation details of the most important Deep Learning algorithms for Time Series Forecasting.

In forecasting spatially-determined phenomena (the weather, say, or the next frame in a movie), we want to model temporal evolution, ideally using recurrence relations. At the same time, we'd like to ...

Rethinking Attention with Performers

Posted by Krzysztof Choromanski and Lucy Colwell, Research Scientists, Google Research Transformer models have achieved state-of-the-art...

Easy Machine Translation with Machine Learning and HuggingFace Transformers

Machine Translation with Python and Transformers - learn how to build an easy pipeline for translation and to extend it to more languages.

Building Neural Networks with Python Code and Math in Detail — II

In the first part of our tutorial on neural networks, we explained the basic concepts about neural networks, from the math behind them to implementing neural networks in Python without any hidden…

Markov Chain

Markov chains are used to model probabilities using information that can be encoded in the current state. Something transitions from one state to another semi-randomly, or stochastically.