Machine Learning part 2
Certification by GRADSKEY
- Foundation
- Medium
- Certificate
Machine Learning II
Syllabus
65 hours of intractive online class.
Module 1: Advanced Supervised Learning |
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Decision Tree Algorithms |
Random Forest Techniques |
Support Vector Machines (SVM) |
Ensemble Learning Methods |
Module 2: Advanced Unsupervised Learning |
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K-Means Clustering |
Hierarchical Clustering |
DBSCAN Clustering |
Module 3: Deep Learning Architectures |
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Artificial Neural Networks (ANN) |
Convolutional Neural Networks (CNN) |
Recurrent Neural Networks (RNN) |
Module 4: Natural Language Processing |
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Text Preprocessing Techniques |
Tokenization and Stemming |
Sentiment Analysis |
Language Models |
Module 5: Computer Vision |
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Image Processing Fundamentals |
Image Classification |
Object Detection |
Image Segmentation |
Module 6: Reinforcement Learning |
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Fundamentals of Reinforcement Learning |
Markov Decision Processes |
Q-Learning Algorithm |
Applications of Reinforcement Learning |
Module 7: Model Deployment and MLOps |
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Model Serialization and Saving |
Deployment Techniques |
Monitoring and Maintenance |
Introduction to MLOps |
Module 8: Emerging Trends in Machine Learning |
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Generative AI Models |
Transfer Learning |
Explainable AI (XAI) |
Future Directions in Machine Learning |
Instructor
Corporate Instructors
From Premier Companies.
“Instructors are from Corporate – Software Engineers from premium companies, working on the cutting-edge technologies and Java on a day to day basis..”
What Our Learners Say
