Naive Bayes Algorithm is one of the most famous supervised machine learning algorithms for the multi-classification problems.

Some of its applications


First step of in computer vision using Sequential API

TensorFlow

TensorFlow as being described in its official website is an end-to-end open source platform for machine learning. …


Common technique in Machine Learning systems used to handle a sequence of data processing components or if there are many transformations have to be applied on these data.

Pipe line in Machine Learning

In Fig.1 you can see that the data output from the price prediction model is being stored…


What Does Deep-Learning Mean?

Deep learning is a subset of machine learning which in-turn is a subset of artificial intelligence as shown in Fig.1, . Deep learning (DL) differs from machine learning (ML) — also called shallow learning — that it offered better performance on many problems by utilizing a huge number of neural…


Back_propagation

Tip: You should have good understanding of what is supervised machine learning, what is training data and testing data. (Also, I prefer to read the first part of this topic


Feed-Forward Neural Networks (FFNN)

INTRODUCTION

In its most general form, a neural network is a machine that is designed to model the way in which the brain performs a particular task or function of interest; the network is usually implemented by using electronic components or is simulated in software on a…


Random Forest & Gradient Boosting Algorithms

Tip It’s recommended that you should read the following articles regarding “Decision Tree: Regression Trees” and ”Decision Trees Classifier” before going deep in ensemble methods.

Introduction

The basic idea behind ensemble methods is to build a group or ensemble of different predictive models -weak models- (each of these models is independent…


Both of Regression Trees and Classification Trees are a part of CART (Classification And Regression Tree) Algorithm. As we mentioned in Regression Trees article, tree is composed of 3-major parts; root-node, decision-node and terminal/leaf-node.

The criteria used here in node splitting differs from that being used in Regression Trees. …


SVM non-linear models and kernel-tricks

In the first part of this tutorial regarding SVM-algorithm linear model which I strongly recommend to read first, it was mentioned that SVM is used for solving both regression and classification problems and mostly used for classification as it has a great ability to classify by using either linear or…


Linear Model

Introduction

In machine learning, support vector machines (SVMs; also, support vector networks) are supervised learning models with associated learning algorithms that analyze data and recognize patterns used for classification and regression analysis but mostly with classification analysis. It works by establishing a hyperplane between different classes of data. …

Ahmed Imam

Machine Learning Engineer & Python/Machine Learning Senior Instructor

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