• Understand Machine Learning
  • Use Cases Walkthrough
  • Machine Learning Techniques
  • Describe Clustering
  • Analyze Clustering Scenarios using Clustering Algorithms
  • Learn TF-IDF and cosine Similarity
  • Understand Supervised Learning Technique
  • Classification
  • Recommendation
  • Learn Decision Tree Classifier
  • Implement how various Decision Tree algorithms work.
  • Implement Application of Techniques on a smaller datasets for better understanding using R.
  • Understand Unsupervised Learning Technique
  • Understand the implementation of Random Forest Classifier
  • Understand the implementation of Na-ve Bayer’s Classifier
  • Apply both techniques on smaller datasets using R
  • Understand Association Rule Mining