Machine Learning
Quality, not quantity
In this 4-week program, we focus on the comprehensive implementation of machine learning algorithms. Participants can choose any two algorithms they wish to master, and the training will concentrate on those selections. The program covers all critical stages, including data extraction, feature engineering, feature preprocessing, feature selection, model training, and model evaluation. By the end of the course, you will have hands-on experience and a deep understanding of the chosen algorithms, equipping you with the practical skills needed to excel in the field of machine learning.
Content
Basic Knowledge of ML required
End- to- end ML model implementation in 4 weeks (2.5 Hours Each)
Week 1: Introduction to Machine Learning
Overview of Machine Learning and Program Structure
Introduction to ML concepts and workflow
Overview of selected algorithms
Data Extraction Techniques
Understanding data sources and formats
Hands-on practice with data extraction tools (e.g., SQL, web scraping)
Case studies and practical exercises
Week 2: Feature Engineering and Preprocessing
Feature Engineering
Creating new features from raw data
Handling missing values and outliers
Practical exercises on feature creation
Feature Preprocessing
Normalization and standardization techniques
Encoding categorical variables
Practical exercises on data preprocessing
Week 3: Feature Selection and Model Training
Feature Selection Methods
Introduction to feature selection techniques
Implementing and evaluating feature selection methods
Practical exercises on selecting optimal features
Model Training
Training the selected algorithms with prepared data
Understanding hyperparameters and tuning
Hands-on practice with model training
Week 4: Model Evaluation and Final Project
Model Evaluation Techniques
Evaluating model performance using various metrics
Cross-validation and model validation methods
Practical exercises on model evaluation
Final Project and Presentation
End-to-end implementation of chosen algorithms
Preparing a report and presentation of results
Feedback and Q&A session
Miscellaneous: Doubts session