Machine Learning
Industry-level machine learning training offers a comprehensive and hands-on learning experience for individuals looking to establish themselves in the dynamic field of machine learning and artificial intelligence. Covering foundational to advanced concepts, this training emphasizes practical applications in real-world scenarios and industry best practices. Participants delve into key machine learning algorithms, statistical modeling, and data preprocessing techniques. By focusing on real-world case studies and projects, participants gain the skills necessary to approach and solve complex problems in various domains. Overall, this training equips individuals to contribute effectively to the rapidly evolving field of machine learning in industry settings.
Syllabus
- Defining Machine Learning and its applications
- Overview of supervised and unsupervised learning
- Real-world examples and case studies
- Introduction to ML algorithms
- Understanding supervised learning
- Basics of regression: Linear and logistic regression
- Hands-on exercises with beginner-friendly ML tools
- Practical applications in regression
- Overview of unsupervised learning
- Introduction to clustering algorithms (k-means, hierarchical)
- Hands-on clustering exercises
- Real-world applications of clustering
- Importance of feature engineering in ML
- Evaluating ML models: Accuracy, precision, recall
- Avoiding overfitting and underfitting
- Practical tips for improving model performance
- Basics of neural networks and deep learning
- Overview of neural network architectures
- Final hands-on project: Implementing a basic ML application
- Presenting and sharing insights from final projects
- Hands on experience with real time projects
- Industry recognized course certificate
- Placement Assistance