Fundamentals of Machine Learning Syllabus — Government College of Eng…
Full syllabus, topics and curated resources for Fundamentals of Machine Learning (Government College of Engineering and Technology, Jammu).
Python programming, machine learning fundamentals, regression, classification and unsupervised learning
- Subject code: CST3404
- University: Government College of Engineering and Technology, Jammu
- Course: BE (2022 onwards)
- Branch: CE
- Semester: 4
Fundamentals of Machine Learning syllabus
Unit 1: Introduction to Python
- Data Types
- Operators and Expressions
- Indexing and Slicing
- Strings
- Conditionals
- Functions
- Control Flow
- Nested Loops
- Sets and Dictionaries
Unit 2: Introduction to Machine Learning and Python Libraries
- Machine Learning versus Statistical Modelling
- Supervised and Unsupervised Learning
- Supervised Learning Classification
- Unsupervised Learning
- Reinforcement Learning
- Applications of Machine Learning
- Pandas
- NumPy
- Scikit-learn
- Matplotlib
Unit 3: Regression
- Simple Linear Regression
- Multiple Linear Regression
- Non-Linear Regression
- Model Evaluation in Regression
- Evaluation Metrics in Regression
Unit 4: Classification and Unsupervised Learning
- Introduction to Classification
- K-Nearest Neighbor
- Decision Trees
- Logistic Regression
- Support Vector Machines
- Logistic Regression versus Linear Regression
- Evaluation Metrics in Classification
- Clustering
- K-Means Clustering
- Hierarchical Clustering
- Density-Based Clustering
- Content-Based Recommender Systems
- Collaborative Filtering