We are currently experiencing changes in the way to solve problems as software engineers. With changes, different feelings emerge: fear, excitement, anxiety, hope… Are we going to be replaced by machines? when? this year? next? in ten years? What’s going to be replaced? Are we going to be deemed useless? I personally don’t think we […]

Why are we going to need a private and custom personal AI

There’s been an explosion after the public launch of ChatGPT, followed by the leakage of the LLaMA weights and the open access to a OpenAI API. LLM’s enabled an incredible amount of applications that couldn’t be done before or at least not with the current level of success. Human language is going to become the […]

Using Rasa NLU for entities extraction (NER)

Rasa is an open source library for building conversational interfaces, most commonly called “chatbots”. Building a good chatbot is not an easy task and people at Rasa knows it, that’s why their library contains a lot of different components working together. One of these components is the NLU (Natural Language Understanding) that resulted to be […]

Métricas de evaluación en pocas palabras

Las métricas de evaluación de un modelo son un tema que siempre trae confusión a la hora de analizar la viabilidad de un proyecto. La mayor parte de las veces hay un foco casi total en lograr un cierto nivel de accuracy, pero en general es un valor que no importa tanto como otros. En […]

Usando Rasa para extraer entidades (NER)

Rasa es una librería open source para construir interfaces conversacionales, más comunmente llamadas “chatbots”. Crear un chatbot que funcione realmente bien no es tarea fácil y la gente de Rasa lo sabe, por lo que su librería contiene muchos componentes que en conjunto permiten crear buenas experiencias conversacionales. Uno de esos componentes es el de […]

Detecting taxis from my balcony

[DISCLAIMER] This is a post from 2017 that I’ve recently translated from Spanish to English. [/DISCLAIMER] I’m doing the Deep Learning for Coders MOOC from and the exercise in the first week consists on using a script to detect dogs and cats from several images. It’s always nice to apply what you learn in […]

A few resources to get into Deep Learning

Before making some recommendations I’d like to mention that I don’t have the absolute truth, this is simply a path that resonates with me because my personality is geared towards more practical resources. I usually like to delve into theory after I know the basics. Now that I made that clear, these are some resources […]

I have a small dataset…so what?

It’s widely known that one of the higher barriers to train a predictive model using Deep Learning is the availability of a large and proper labeled dataset as it usually carries a high time labeling cost to get it. So we have two high cost tasks right here and before getting to the fancy stage […]

Detección de fraudes con ML desde cero

Hace unas semanas me pidieron un pequeño informe (que no lleve mucho tiempo) a alto nivel de como implementaría la funcionalidad de detección de fraudes usando Machine Learning. Mi aclaración fue de que no soy un experto en el mundo de detección de fraudes y por lo tanto que mi enfoque puede no ser el […]

NLP techniques and the balance between model accuracy and explainability

If you’re working on a NLP related task, you’ll need to decide which approach to take. Before starting building the code a project structure, it’s important for you to define the specific goals of the project in terms of explainability and accuracy. Nowadays the NLP techniques that can offer more accuracy are the ones with […]