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Giuseppe Bonaccorso
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Avanti. Inevitabilmente avanti.
Avanti. Inevitabilmente avanti.

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A book that every data scientist should read

I would like to suggest the book Factfulness (by Hans Rosling) to every data scientist and every student who wishes to start this career. It’s not a technical book full of formulas, algorithms, and other complex stuff. Only a few plots and a lot of…
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Fundamentals of Machine Learning with Scikit-Learn #MachineLearning #Python #ScikitLearn

A tutorial video (2 hours) derived from the book Machine Learning Algorithms has been released: Fundamental of Machine Learning with Scikit-Learn: From the notes: As the amount of data continues to grow at an almost incomprehensible rate, being able to…
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Getting Started with NLP and Deep Learning with Python

A tutorial video (2 hours) derived from the book Machine Learning Algorithms has been released: Getting Started with NLP and  Deep Learning with Python. From the notes: As the amount of data continues to grow at an almost incomprehensible rate, being able…
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Hetero-Associative Memories for Non Experts: How "Stories" are memorized with Image-associations. #MachineLearning #Deep Learning #AI

Think about walking along a beach. A small kiosk-bar has its radio turned-on and a local DJ announces an 80’s song. Immediately, the image of a car comes to your mind. It’s your first car, a second-hand blue spider. While listening to the same song, you…
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A glimpse into the Self-Organizing Maps (SOM) #MachineLearning

Self-Organizing Maps (SOM) are neural structures proposed for the first time by the computer scientist T. Kohonen in the late 1980s (that’s why they are also known as Kohonen Networks). Their peculiarities are the ability to auto-cluster data according to…
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ML Algorithms addendum: Passive Aggressive Algorithms

Passive Aggressive Algorithms are a family of online learning algorithms (for both classification and regression) proposed by Crammer at al. The idea is very simple and their performance has been proofed to be superior to many other alternative methods.…
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A Brief (and Comprehensive) Guide to Stochastic Gradient Descent Algorithms

Stochastic Gradient Descent (SGD) is a very powerful technique, currently employed to optimize all deep learning models. However, the vanilla algorithm has many limitations, in particular when the system is ill-conditioned and could never find the global…
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A virtual Jacques Lacan discusses about Artificial Intelligence

“In other words, the man who is born into existence deals first with language; this is a given. He is even caught in it before his birth.” (J. Lacan)   A virtual discussion with Jacques Lacan is a very hard task, above all when the main topic is…
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Linear Separable? No? For me it is! A Brief introduction to Kernel Methods

This is a crash-introduction to kernel methods and the best thing to do is starting with a very simple question? Is this bidimensional set linearly separable? Of course, the answer is yes, it is. Why? A dataset defined in a subspace Ω ⊆ ℜn is linearly…
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