# An introduction to Gradient Descent Algorithm

Gradient Descent is one of the most used algorithms in Machine Learning and Deep Learning.

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# Category: Machine Learning

# An introduction to Gradient Descent Algorithm

# From my talk for Google I/O extended in Guatemala

# Simple guide to Confusion Matrix

# L0 Norm, L1 Norm, L2 Norm & L-Infinity Norm

# Easy and quick explanation: Naive Bayes algorithm

Gradient Descent is one of the most used algorithms in Machine Learning and Deep Learning.

On past April 9th, I gave a talk for the Google I/O extended in Guatemala about Google Colaboratory.

Putting it in a few words, a confusion matrix is a summarization of the performance of an algorithm. It is a table that describes the performance of a classifier model with known labels.

First of all, what is a Norm? In Linear Algebra, a Norm refers to the total length of all the vectors in a space.

Naive Bayes is one of the simplest yet reliable algorithms used in Machine Learning, particularly in Natural Language Processing (NLP) problems.

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