- 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