Recent Posts

  • Episode 27: Techstars accelerator and the culture of fireflies

    In the aftermath of the Barclays Accelerator, powered by Techstars experience, one of the most innovative and influential startup accelerators in the world, I’d like to give back to the community lessons learned, including the need for confidence, soft-s...

  • Episode 26: Deep Learning and Alzheimer

    In this episode I speak about Deep Learning technology applied to Alzheimer disorder prediction. I had a great chat with Saman Sarraf, machine learning engineer at Konica Minolta, former lab manager at the Rotman Research Institute at Baycrest, Universit...

  • Episode 25: How to become data scientist [RB]

    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

  • Episode 24: How to handle imbalanced datasets

    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 belong to one class is significantly lower than those...

  • Episode 23: Why do ensemble methods work?

    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 building a number of single classifiers and then combining o...

  • Episode 22: Parallelising and distributing Deep Learning

    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 deep learning on relatively large clusters. As a matt...

  • Episode 21: Additional optimisation strategies for deep learning

    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 convergence of a minimisation method for deep learning. I explor...

  • Episode 20: How to master optimisation in deep learning

    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 optimisation methods and explain which one is the best and why...

  • Episode 19: How to completely change your data analytics strategy with deep learning

    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 recently, neural network models started to be applied als...

  • Episode 18: Machines that learn like humans

    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 beings do, faster, and more efficiently

Data Science

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