Batch 2 Machine learning

15 days course

📍 Live Classes on Zoom

📍1st class : 6 Oct 2025 8 pm PKT

📍 Fee for full course: 400rmb/60USD (50 % for already registered Participants)

📆 Schedule: Monday to Thursday

📌 Seats: 10 ✅ Filled: 3 🟢 Remaining: 7

⏳ Last Date to Register: 6 Oct 2025

https://chat.whatsapp.com/ICMJlpT0ZBi5ze7iJDC2Vu?mode=ems_copy_t

📲 Join WhatsApp Group for Demo Class

Module 1: Introduction to Machine Learning

- Overview of machine learning

- Types of machine learning (supervised, unsupervised, reinforcement)

- Machine learning workflow

- Basic math concepts (linear algebra, probability, statistics)

Module 2: Supervised Learning

- Linear regression

- Logistic regression

- Decision trees

- Random forests

- Support vector machines (SVMs)

- Model evaluation metrics (mean squared error, accuracy, precision, recall, F1 score)

Module 3: Model Evaluation and Hyperparameter Tuning

- Cross-validation

- Hyperparameter tuning (grid search, random search)

- Model selection and ensemble methods

- Overfitting and regularization

Module 4: Unsupervised Learning

- Clustering (k-means, hierarchical)

- Dimensionality reduction (PCA, t-SNE)

- Anomaly detection

Module 5: Deep Learning

- Introduction to neural networks

- Feedforward neural networks

- Convolutional neural networks (CNNs)

- Recurrent neural networks (RNNs)

- Long short-term memory (LSTM) networks

Module 6: Advanced Topics

- Transfer learning

- Generative adversarial networks (GANs)

- Natural language processing (NLP)

- Time series forecasting

Module 7: Research Applications

- Applying machine learning to research problems

- Working with imbalanced datasets

- Handling missing data

- Interpreting results and communicating findings

Module 8: Project Development and Presentation

- Students will work on a research project applying machine learning techniques

- Project presentations