Download Udemy – Numerical Methods and Optimization in Python 2022-4

Numerical Methods and Optimization in Python

Description

Numerical Methods and Optimization in Python, the course of numerical methods and optimization in Python, has been published by Udemy Academy. This course is about numerical methods and optimization algorithms in Python programming language. We do not intend to discuss all the theories related to numerical methods (for example, how to solve differential equations, etc.) – we only want to consider concrete implementations and numerical principles. The first part is about matrix algebra and linear systems such as matrix multiplication, Gaussian elimination and applications of these methods.

Next, we examine the famous Google PageRank algorithm. Then we will talk about numerical integration. How to use techniques such as trapezoidal rule, Simpson’s formula and Monte Carlo method to calculate the definite integral of a given function. The next chapter is about solving differential equations with Eulerian method and Runge-Kutta method. We consider examples such as the pendulum and ballistic problem. Finally, we are going to explore optimization techniques related to machine learning: stochastic gradient descent algorithm, ADAGrad, RMSProp and ADAM optimizer.

What you will learn

  • Understanding linear systems and Gaussian elimination
  • Understanding vectors and eigenvalues
  • Know the Google PageRank algorithm
  • Understand numerical integration
  • Understand Monte Carlo simulations
  • Familiarity with differential equations – Eulerian method and Runge-Kutta method
  • Familiarity with optimization algorithms related to machine learning (gradient descent, stochastic gradient descent, ADAM optimizer, etc.)

Who is this course suitable for?

  • This course is for students with a quantitative background or software engineers who are interested in numerical methods.

Specifications of the course Numerical Methods and Optimization in Python

  • Publisher: Udemy
  • teacher : Holczer Balazs
  • English language
  • Education level: all levels
  • Number of courses: 161
  • Training duration: 13 hours and 58 minutes

Chapters of the Numerical Methods and Optimization in Python course

Course prerequisites

  • Mathematical background – differential equations, integration and matrix algebra

Pictures

Numerical Methods and Optimization in Python

Sample video

Installation guide

After Extract, view with your favorite Player.

English subtitle

Quality: 720p

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 797 MB

File(s) password: www.downloadly.ir

Size

2.77 GB

4.2/5 – (2621 points)

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