Machine learning is a set of effective methodologies to perform useful predictions in many areas, including artificial intelligence.
I strongly believe in sharing knowledge as a key element to spread the collective awareness about innovation: this is the main reason I created this blog.


AI inspiration

I am working on a new book. I’d like to talk about the benefit of machine learning for practical applications useful for many organizations.

Please stay tuned!


OpenAI Whisper: the Open Source ASR based on Transformers

As described on the official OpenAI website, Whisper is an Automatic Speech Recognition (ASR) system trained on 680,000 hours of supervised multilingual and multitasking data collected from around the web. The use of such a large and diverse data set leads to greater robustness in speech recognition even in the presence of particular accents, accentuated …

MLOps scalability

Nowadays Machine Learning (ML) techniques are applied in various industries, along with an increasing number of projects and complexity. This generates on one hand the need for greater governance, i.e. the ability to orchestrate and control the development and deploy over the entire ML life cycle (preprocessing, model training, testing, deployment), on the other hand, …

Recurrent Neural Networks for Sentiment Analysis

We described in one of the previous posts how to use convolutional neural networks, in order to perform speech recognition related to simple numbers from zero to nine. In practice, speech recognition has superior performance by adopting particular neural networks called Recurrent Neural Networks, or simply RNNs. Unlike “simple” feed-forward neural networks, RNNs process as …