So how many times do you ask Siri, Alexa, or Google for the weather or the time? Several kinds of bots are now in the market, some more complex capable of having a continuous conversation, and other ones that just do some pre-program actions. In this post, I will show…


In today's post, I will share some of the most used Metrics Functions in Keras during the training process. A Metric Function is a value that we want to calculate in each epoch to analyze the training process online. …


An ELMO layer implementation using TensorFlow-Hub and how to prepare data for any NLP task.

ELMo (em-beddings from Language Models) is a deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i.e., to…


BERT (Bidirectional Encoder Representations from Transformers) is a recent paper published by researchers at Google AI Language. BERT’s key technical innovation is applying the bidirectional training of the Transformer, a popular attention model, to language modeling. This is in contrast to previous efforts that looked at a text sequence either…


In this post, I will show my learning rate decay implementation on Tensorflow Keras based on the cosine function.

One of the most difficult parameters to set while training any deep learning model is the learning rate. If it is a big value the weights of the model will begin…


Implementation in TensorFlow and Keras of Bilinear CNN Models for Fine-grained Visual Recognition, paper.

FINE-GRAINED recognition tasks generally involve discrimination between categories that have a shared structure but differ in subtle ways, distinguishing between a “Toyota Prius” and a “Toyota corolla”. …


Implementation of BOW, TF-IDF, word2vec, GLOVE and own embeddings for sentiment analysis. This approach can be replicated for any NLP task.

The object of this post is to show some of the top NLP solutions specific in deep learning and some in classical machine learning methods. This a compilation of…

Sebastian Correa

Engineer with experience in machine learning, neural networks, deep learning. Specialized in pattern recognition, NPL and computer vision.

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