Applied Machine Learning Methods (Using R)

Applied Machine Learning Methods (Using R)

  • Course level: Intermediate  
There are no active Semester Schedule for this course   Pre-registar

Description

This course is designed for data professionals in intermediate level who are interested to build machine learning algorithms and predictive models with R in real data analysis projects.

COURSE OBJECTIVES

•To improve your knowledge on machine learning and AI
•To build the robust predictive analytics models
•To improve the accuracy of machine learning models
•To know how to choose the most related Machine Learning

model in real projects

COURSE SYLLABUS

•Fundamentals of Machine Learning
•Machine Learning pipeline
•Underfitting, Overfitting and Generalization
•Data preprocessing and visualization
•Machine Learning - Statistics essentials
•Supervised and unsupervised algorithms
•All Regression algorithms
•Decision Trees and ensembling methods
•K-Nearest Neighbors (K-NN)
•Support Vector Machine (SVM)
•Naive Bayes
•K-Means Clustering
•Hierarchical Clustering
•Dimensionality Reduction
•Bias vs Variance Tradeoff
•Model Evaluation and Performance
•Introduction to Advanced Machine

Learning – Reinforcement

Learning and Deep Learning

Registration fee :
€ 590

Target audience

  • IT professionals
  • Computer Science and IT Students
  • Data Scientists
  • Data Analysts
  • Technical managers

Requirements

  • Basic knowledge of R and R
  • Studio
  • Basic knowledge of descriptive statistics and mathematics