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The Complete Ensemble Learning Course 2021 With Python

June 22, 2021
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The Complete Ensemble Learning Course 2021 With Python Learn to create Ensemble Learning Algorithms in Python with Real World example on practical ways
The Complete Ensemble Learning Course 2021 With Python Learn to create Ensemble Learning Algorithms in Python with Real World example on practical ways

The Complete Ensemble Learning Course 2021 With Python

Learn to create Ensemble Learning Algorithms in Python with Real World example on practical ways

What you’ll learn

The Complete Ensemble Learning Course 2021 With Python

  • Support vector machines
  • Logistic Regression Implementation
  • Decision trees
  • K-Nearest Neighbors
  • K-means
  • Hard and soft voting
  • Meta-Learning
  • Base learners and meta-learner
  • Bootstrapping
  • Bagging
  • AdaBoost
  • Gradient boosting
  • XGBoost
  • Forest trees
  • Random forests
  • Extra trees
  • Keras.
  • Pandas.
  • Matplotlib.

Requirements

  • Basic knowledge of machine learning
  • Basic knowledge of Python
  • But everything will be taught from the roundup.

Description

Welcome to The Complete Ensemble Learning Course 2021 With Python

Interested in the field of Machine Learning? Then this course is for you!

This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:

  • Section 1: Introduction.
  • Section 2: Basic Machine Learning concept
  • The Section 3: Basic Ensemble Learning concept
  • Section 4: Voting Method
  • Section 5: Stacking Method
  • The Section 6: Bagging Method
  • Section 7: Boosting Method
  • Section 8: Random Forests.
  • The Section 9: Clustering
  • Section 10: Predicting Bitcoin Prices – REAL-WORLD PROBLEMS
  • Section 11: Movie Recommendation system -REAL-WORLD PROBLEMS

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are two big projects one-three small projects to practice what you have learned throughout the course. These projects are listed below:

  • Handwritten Digit.
  • Breast Cancer Detection
  • Diabetes Prediction
  • Bitcoin Predictions
  • Movie Recommendation system

Become a machine learning guru today! I will see you inside the course!

Who this course is for:

  • Anyone interested in Deep Learning, Machine Learning and Ensemble Learning
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning, and Ensemble Learning
  • Any intermediate-level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any students in college who want to start a career in Data Science.
  • AI experts who want to expand on the field of applications.
  • Data Scientists who want to take their AI Skills to the next level.
  • Anyone passionate about Machine Learning and Ensemble Learning.
  • Last updated 5/2021

Content From: https://www.udemy.com/course/the-complete-ensemble-learning-course-2021-with-python/
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