This is an informative article that details notable AI techniques and algorithms. It mentions the latest happenings in AI development along with the high-level understanding of present techniques. The article offers simple descriptions and creative analogies, making it readable for enthusiasts, learners and AI practitioners.
This technical read offer knowledge around a variety of neural network architecture. It talks about such as RNN (Recurrent Neural Network), LSTM (Long short term memory) and attention mechanism. The main content of the article is around Transformer architecture that was released in 2017. This article is more of a digest of technical inner workings of transformer architecture.
This article mostly focuses on the impact of ML tools and libraries. The article provides a detailed blueprint on how ML projects are structured. This is much recommended read for self-taught ML engineers and those undergoing institutional education. In this article, the author has offered a recipe for developing the right understanding to have successful ML career.