Course Content:
- Introduction
- Motivational Lecture
- Course Introduction
- Success stories
- Job market
- Course Applications
- Institute/work ethics
- Introduction to Artificial Intelligence
- A brief history of AI
- AI terminology
- State of the art techniques
- Lab Installation for python language
- Machine Learning Fundamentals
- What is Data?
- What is Machine Learning?
- Supervised vs. Unsupervised learning?
- Evaluation Train
- Test Split Validation
- Regression
- Regression Univariate
- Linear Regression
- Multivariate Regression
- Classification
- Algorithms
- KNN Naïve Bayes
- Decision Trees
- SVMs
- Clustering
- Clustering Classification vs. Clustering K-means
- Clustering
- Time Series Analysis
- MLP Feed
- Forward Neural Networks
- Neural Networks
- Applications with Computer Vision
- Classification and Detection