Data Science at Home

Technology, machine learning and algorithms

Episodes Date

In this episode, I speak about the requirements and the skills to become data scientist and join an amazing community that is changing the world with data analyticsa
October 16, 2017
In machine learning and data science in general it is very common to deal at some point with imbalanced datasets and class distributions. This is the typical case where the number of observations that...
October 8, 2017
Ensemble methods have been designed to improve the performance of the single model, when the single model is not very accurate. According to the general definition of ensembling, it consists in buildi...
October 3, 2017
Continuing the discussion of the last two episodes, there is one more aspect of deep learning that I would love to consider and therefore left as a full episode, that is parallelising and distributing...
September 25, 2017
In the last episode How to master optimisation in deep learning I explained some of the most challenging tasks of deep learning and some methodologies and algorithms to improve the speed of convergen...
September 18, 2017
The secret behind deep learning is not really a secret. It is function optimisation. What a neural network essentially does, is optimising a function. In this episode I illustrate a number of optimisa...
August 28, 2017
Over the past few years, neural networks have re-emerged as powerful machine-learning models, reaching state-of-the-art results in several fields like image recognition and speech processing. More rec...
August 9, 2017
Artificial Intelligence allow machines to learn patterns from data. The way humans learn however is different and more efficient. With Lifelong Machine Learning, machines can learn the way human being...
March 28, 2017
Talking about security of communication and privacy is never enough, especially when political instabilities are driving leaders towards decisions that will affect people on a global scale
February 15, 2017
We strongly believe 2017 will be a very interesting year for data science and artificial intelligence. Let me tell you what I expect and why.
December 23, 2016

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