Invitation to neural networks
The course is an invitation to the use of neural networks for binary classification problems, our main example of algorithm is the perceptron algorithm, the course is divided into classes of the
Following way:

What is Machine Learning?

A look at Python

Formal description of the Perceptron algorithm

Implementation of the perceptron algorithm for image classification

Neural networks in general.
Syllabus

Introduction

What is Machine Learning?

Mathematical notation


Python installation and a working environment for MachineLearning

Minimicrowave installation

Installation for Windows.

Installation for MacOS

Installation for Linux

Creation of a virtual environment for data analysis

Disable the base environment

Creation of a specific environment for data analysis using condaforge


Perceptron

Theoretical justification of the algorithm of the perceptron


Binary classifier of microscopic images

Neural Networks

Expressive ability

Almost linearly separable data

Gradient method

Margin, overadjustment and regularization

Convolutional neural networks and other activation functions

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