The World has been talking about the next set of excitements on Machine Learning & Artificial Intelligence .
This course is focused on specific topics of Supervised and Unsupervised Machine Learning & the practical Problems for the participants who already have a fair amount of knowledge of Machine Learning and have been working in the field of Machine Learning & Analytics.
- Definition of Supervised and Unsupervised Machine Learning
- Supervised and unsupervised learning with a real-life example
- Types of Supervised and Unsupervised Machine LearningAlgorithms
- Classification and regression supervised learning
- Clustering and association unsupervised learning
- Algorithms used for supervised and unsupervised - Machine Learning Algorithms Mindmap
- Practical problems to Supervised and Unsupervised Machine Learning
- Learning from the know label data to create a model then predicting target class for the given input data Vs Learning from the unlabeled data to differentiating the given input data
- Case study (BFSI & Pharma )
Who is the target audience?
- Corporate Executives looking to learn this technology & implement in his/her projects
- Consultants and Professional Service Providers
- CEO's, Boards, and Senior VP's
- Technology Enthusiasts
- Anyone who’s looking for a shift in his/her career
This should be both online-based; For Corporate or more than 12 & less than 15 in a group can be classroom based.
The way World is shaping up
- Current Exciting Scenarios
- Statistics brush up
- Intro to Data types & Data Classification
- classification & Regression
- • Decision trees • Support vector machine (SVM) • k-Nearest Neighbors • Naive Bayes • Random forest • Linear regression • polynomial regression • SVM for regression
- Clustering & Markov Models
- Hierarchical clustering
- Industry-centric approaches
- Case Study
- Current scenarios - The way world is shaping up
- Getting started with concepts of Supervised and Unsupervised Machine Learning
- Supervised and Unsupervised Machine learning tools, design & advice for best suited to Industries
- Regression & Classification – Supervised learning & Unsupervised learning - Use cases
- Best practices