Machine Learning with Python - Entropy and Information Gain

Entropy and information gain in Machine Learning

In machine learning, entropy and information gain are fundamental concepts used in decision trees and supervised learning to make data division decisions during the training process of a model. These concepts are often associated with the Iterative Dichotomiser 3 (ID3) algorithm and its variants, such as

Machine Learning with Python - CHAID h

The CHAID algorithm in Machine Learning with Python

CHAID (Chi-squared Automatic Interaction Detector) is an algorithm used for building decision trees, in particular for splitting variables based on their interactions with target variables. Unlike traditional decision trees, which rely primarily on the Gini index or entropy to choose splits, CHAID uses chi-square tests to automatically determine optimal splits.

Machine Learning with Python - Gradient Boosting

Gradient Boosting in Machine Learning with Python

The Gradient Boosting algorithm is a machine learning technique that builds a predictive model by combining several weaker models (usually decision trees) together into a single strong structure. The main goal of Gradient Boosting is to progressively improve the weaknesses of weak models, allowing you to create a stronger and more adaptable model.

Deep Learning

Deep Learning

Deep learning is a computational technique that allows you to extract and transform data from sources such as human speech or image classification, using multiple layers of neural networks. Each of these layers takes its inputs from the previous layers and refines them, so progressively. The layers are trained by algorithms that minimize their errors and improve their accuracy. In this way the networks learn to perform specific tasks.

WaveNet and Text-To-Speech (TTS) machines can speak m

 WaveNet and Text-To-Speech (TTS) – machines can speak

   The progress of this last year regarding Deep Learning is truly exceptional. Many steps forward have been made in many fields of technology thanks to neural networks and among these there is the synthetic voice, or rather the Text-To-Speech (TTS) that is, that series of technologies able to simulate the human way of speaking by reading a text. Among the models realized, therefore, there is WaveNet, a highly innovative model that has revolutionized the way of doing Text-To-Speech making them jump really forward

2017 the year of Deep Learning frameworks

 2017 The year of Deep Learning frameworks

   2017 was a special year for Deep Learning. In addition to the great experimental results obtained thanks to the algorithms developed, the Deep Learning this year has seen its glory in the release of many frameworks. These are very useful tools for developing numerous projects. In the article you will see an overview of many new frameworks that have been proposed as excellent tools for the development of Deep Learning projects.