Discover China’s biggest AI Model GPT-3 caused a stir a few months ago when it impressed the world with its capabilities for generating text content. Its 175 Billion parameters made it look like a true AI giant. Now a new Deep Learning model is making an appearance at an AI…

What is it, why does it matter, and its main challenges — Introduction Nowadays, all over the internet, you can find all kinds of resources addressing the science and methodologies to successfully develop a machine learning model. …

Keys to Read and Comprehend a Paper The Right Way — Introduction Throughout this post, we will review the most important principles you should take into account when reading a machine learning paper and if you actually need to read papers to advance in your path as Machine Learning Engineer/Practitioner. What is a Paper? A paper is a written article, but not a journalist one or…

Drastically Increment Your Value Contribution and Business Understanding with this Must-Read Book — Introduction and Motivation Thanks to Data Science and Machine Learning, just by writing a few lines of code, we are able to build a model able to detect and classify objects in images, to build a movie recommender system, or to predict the price of a house merely by introducing its characteristics.

Boost up your knowledge and career with this gem — Introduction Throughout this post, we will cover a review of one of the best books you should add to your repertoire to increase your skillset and boost up your Data Science career. As you already know (and I previously discussed in other posts), Data Science is a passionate and multidisciplinary field…

Understand the intuition behind RNN! — Introduction The goal of this article is to explore Recurrent Neural Networks in-depth, which are a kind of Neural Networks with a different architecture than the ones seen in previous articles (Link). Concretely, the article is segmented in the following parts: What RNNs are Long Short-Term Memory (LSTM) networks Implementation of…

Learn how to take your Deep Learning models to the next level! Introduction The objective of this article is to learn how to optimize neural networks by selecting the best hyper-parameters. Concretely, we’ll explore: Grid Search Hyperopt Genetic Algorithms Grid Search Grid search is the simplest method of finding the best parameters within…

Learn how to apply these powerful techniques to take your Deep Learning models to a whole new level! Introduction As we have seen in previous articles, we can use the architectures developed by research teams and leverage their power to make predictions and obtain better results in our Deep Learning models. …

Learn about the different available methods, and to select the one most appropriate to solve your problem. Introduction The objective of this article is to explore the different Gradient Descent extensions such as Momentum, Adagrad, RMSprop… In previous articles, we have studied three methods to implement back-propagation in Deep Learning models: …