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# Rubens Zimbres's Blog (8)

### A Cheat Sheet on Probability

Added by Rubens Zimbres on November 21, 2016 at 2:28am — 10 Comments

### Neural Networks: The Backpropagation algorithm in a picture

Here I present the backpropagation algorithm for a continuous target variable and no activation function in hidden layer: although simpler than the one used for the logistic cost function, it's a proficuous field for math lovers.

Added by Rubens Zimbres on November 19, 2016 at 9:30am — 3 Comments

### Matrix Multiplication in Neural Networks

This post is the outcome of my studies in Neural Networks and a sketch for application of the Backpropagation algorithm. It's a binary classification task with N = 4 cases in a Neural Network with a single hidden layer. After the hidden layer and the output layer there are sigmoid activation functions. Different colors were used in the Matrices, same color as the Neural Network structure (bias, input, hidden, output) to make it easier to understand.…

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Added by Rubens Zimbres on November 16, 2016 at 11:00am — 4 Comments

Added by Rubens Zimbres on October 27, 2016 at 7:30am — No Comments

### Tricks in Face Recognition

Last year I started developing a Face Recognition model. I started with static pictures and using Wolfram Mathematica. This year I found out we can do the same job using OpenCV in Python, or creating specific filters in R and applying Weierstrass and Gaussian transformation.

There are lots of difficulties in recognizing faces of the same person, like: position, rotation of face, age, feeling, brightness, gamma, contrast, gamma, saturation, obstacles like hands,hair and so…

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Added by Rubens Zimbres on October 15, 2016 at 4:00am — No Comments

### Theano Tensors Explained in a Picture

Lately I've been doing some experiences with Theano and Deep Learning. One thing that I really thought could help is to understand the workflow of a Theano algorithm through visualization of tensors' connections. After developing the model, I printed the prediction algorithm for a deep learning Neural Net with 2 hidden layers, 2 inputs X1 and X2, and a continuous output Y. I used Graphviz and pydot to generate the graphic with this line of…

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Added by Rubens Zimbres on October 7, 2016 at 3:00am — 3 Comments

## WOLFRAM MATHEMATICA

Before assessing R and Python, I will start with Wolfram Mathematica. It's a powerful software, similar to MatLab. You can handle lists and matrices easily, you have all the best mathematical functions, backup of Wolfram Alpha and extremely sophisticated graphics visualizations, that allow you, for instance, to make and visualize an animated gradient descent, animate different weights for a given neural network, choose a specific…

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Added by Rubens Zimbres on October 3, 2016 at 8:00am — 7 Comments

### Complexity frontiers, Artificial Intelligence and Agent-Based Modeling

Complexity, in my point of view, is the key for disruptive evolutions in Data Science and Machine Learning. Approaches as the one from Edgar Morin allow us to see the world through a completely different point of view, analyzing and deconstructing commom sense, leading to a completely new epistemologic view of the world and problems.

Epistemology deals with fundamentals of truth, Socrates, Plato (the cave), Bachelard, Morin, Descartes and so on. An agent-based model is a model where…

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Added by Rubens Zimbres on June 26, 2016 at 7:01am — No Comments

2016