Advanced Machine Learning Syllabus — Government College of Engineerin…
Full syllabus, topics and curated resources for Advanced Machine Learning (Government College of Engineering and Technology, Jammu).
Advanced feature engineering, ensemble methods, deep learning, NLP and time series forecasting techniques
- Subject code: CST-3801
- University: Government College of Engineering and Technology, Jammu
- Course: BE (2022 onwards)
- Branch: CE
- Semester: 8
Advanced Machine Learning syllabus
Unit 1: Feature Engineering and Pre-processing
- Data Cleaning - Handling Missing Values
- Outlier Detection and Treatment
- Feature Scaling - Normalization and Standardization
- Feature Selection - Filter Methods
- Feature Selection - Wrapper Methods
- Feature Selection - Embedded Methods
- Feature Extraction - PCA
- Feature Extraction - LDA
- Data Transformation - Log Transforms and Polynomial Features
Unit 2: Advanced Models and Ensemble Methods
- Regularization - Ridge Regression
- Regularization - Lasso Regression
- Decision Tree Regression
- Random Forest Regression
- Gradient Boosting Regression
- Multi-Class Classification
- One-vs-Rest (OvR) Classification
- One-vs-One (OvO) Classification
- Ensemble Methods - Bagging
- Ensemble Methods - Boosting
- Ensemble Methods - Stacking and Voting Classifiers
Unit 3: Neural Networks and Deep Learning
- Perceptron and Multi-Layer Perceptron
- Activation Functions
- Deep Learning Frameworks - TensorFlow, Keras and PyTorch
- Backpropagation
- Gradient Descent and Optimizers (SGD, Adam)
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Overfitting and Regularization in Neural Networks
Unit 4: Natural Language Processing (NLP)
- Text Pre-Processing - Tokenization and Stemming
- Text Pre-Processing - Lemmatization and Stopwords
- Vectorization - Bag of Words and TF-IDF
- Word Embeddings - Word2Vec and GloVe
- Text Classification - Sentiment Analysis and Spam Detection
- Sequence Models - RNNs, LSTMs and GRUs