Introduction
Embark on your AI learning journey with our comprehensive Machine Learning course. Gain practical skills to tackle real-world problems without the need for programming. Machine learning, a subset of artificial intelligence (AI), equips computers to learn from data, identifying intricate patterns beyond human comprehension. Our course, featuring a Graphical User Interface (GUI)-based tool, empowers you to delve into regression, classification, and ensemble machine learning algorithms. Learn to solve real-world challenges through a systematic process, covering problem definition, data preparation, algorithm selection, results refinement, and outcome presentation. Upskill and deepen your knowledge in AI with our practical approach.
Course Outline
- Introduction to Machine Learning
- What is Machine Learning
- Machine Learning in Real life
- Types of Machine Learning
- Key ML Models
- Installing Weka
- Load Dataset to Weka
- Build Your First Classifier
- Classification
- What is Classification?
- K-Nearest Neighbours (KNN)
- Support Vector Machine (SVM)
- Naive Bayes
- Decision Tree (DT)
- Regression
- Introduction to Regression
- Linear Regression
- Support Vector Regression
- K-Nearest Neighbour Regression
- Ensemble Methods
- What is Ensemble Methods?
- Bagging
- Random Forest
- Stacking
- Clustering
- What is Clustering?
- K-Means Clustering
- Hierarchical Clustering
- Neural Network
- What is Neural Network?
- Multilayer Perceptron Classifier
- Problem Solving through Machine Learning
- Problem Definition
- Data Conceptualization
- Data Gathering
- Feature Engineering
- Algorithm Spot Check
- Fine Tuning Model
- Pitfalls
