Download Udemy – Ensemble Machine Learning in Python: Random Forest, AdaBoost 2021-10

Ensemble Machine Learning in Python: Random Forest, AdaBoost

Description

Ensemble Machine Learning in Python: Random Forest, AdaBoost, course Collective Machine Learning in Python: Random Forest, AdaBoost is published by Udemy Academy. Machine learning has led to amazing results, such as the ability to analyze medical images and predict diseases to the level of an expert. Using deep reinforcement learning, Google’s AlphaGo program was able to defeat the world champion in the Go strategy game. Machine learning is even being used to program self-driving cars, which are set to change the automotive industry forever. Imagine a world where car accidents were drastically reduced, simply by removing the element of human error. Google has announced that they have put their main focus on machine learning, and companies like NVIDIA and Amazon have followed suit, and this is what will drive innovation in the coming years.

Machine learning is used in many types of products and is used in many industries such as finance, online advertising, medicine and robotics.This course is all about collective methods. You have already been familiar with some classic machine learning models such as K-Nearest neighbor and decision tree and have studied their limitations and drawbacks. But what if we could combine these models to overcome those limitations and produce a more powerful classifier. In this course, you will study methods of combining models such as decision trees and logistic regression to build models that can achieve much higher accuracy than the base models they are built from.

What you will learn

  • Understand and extract the bias-variance combination separation
  • Getting to know the bootstrap method and its application in bagging
  • Understanding why bagging improves classification and regression performance
  • Understand and implement Random Forest
  • Understand and implement AdaBoost

Who is this course suitable for?

  • Learn about the types of models that win machine learning competitions.
  • Students who are learning the machine
  • Professionals who want to apply data science and machine learning to their work
  • Entrepreneurs who want to use data science and machine learning to optimize their business
  • Computer science students who want to learn more about data science and machine learning

Ensemble Machine Learning in Python course specifications: Random Forest, AdaBoost

Beginning of the course seasons on 2023-1

Ensemble Machine Learning in Python course prerequisites: Random Forest, AdaBoost

  • Calculus (derivatives)
  • Numpy, Matplotlib, Sci-Kit Learn
  • K-Nearest Neighbors, Decision Trees
  • Probability and Statistics (undergraduate level)
  • Linear Regression, Logistic Regression

Pictures

Ensemble Machine Learning in Python: Random Forest, AdaBoost

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 – 85.9 MB

File(s) password: www.downloadly.ir

Size

1.08 GB

4.1/5 – (1774 points)

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