MACHINE LEARNING

Advanced Machine Learning in Python

Machine learning teaches computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model.

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About the course

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In machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance that could be obtained from any of the constituent learning algorithms alone. A machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.

In this course you will learn about different Ensemble methods as meta-algorithms that combine several machine learning techniques into one predictive model in order to decrease variance (bagging), bias (boosting), or improve predictions (stacking).

Skills you will gain

  • Ensemble methods
  • Random forests
  • Decision Trees
  • Bagging
  • Boosting
  • Stacking
  • SVM
  • PCA

Course Syllabus

Module 1

Advanced Machine Learning

4.0 Hrs

1 Quiz
  • Determining Neighbours (K) by voting mechanism
  • Approach to find Nearest neighbors and more on Euclidean distance
  • Types of distance, Pros, and Cons of KNN
  • Descriptive Statistics in Python and more on cleaning of data for BC data
  • Functions and Splitting the data in Train and Test set for BC data
  • Confusion matrix in details and improvement in model by plotting through Seaborn library
  • Cleaning data for improvement of model
  • Introduction to Support vector machine and perceptron algorithm
  • Properties of line in perceptron algorithm
  • How SVM looks in 2D space (two dimension)
  • Kernel SVM and Mercers theorem
  • Optimal hyperplane concept
  • SVM code in Python for Character Recognition and types of Kernel
  • Introduction to Decision Trees
  • Ensemble methods
  • Bias-Variance error and bagging-boosting concept
  • Boosting Concept
  • Ensemble for Random Forest
  • Show more

Projects

Identify potential customers for loans

Diagnosing Parkinson's disease using Random Forests

Course certificate

Get Advanced Machine Learning in Python course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.