Machine Learning: Level-01
Introduction to Machine Learning: level-01
Overview:
- Develop skills in model tuning, feature engineering, and using tools like scikit-learn and TensorFlow for predictive analytics.
- Duration: 2 Months
Topics Covered:
- Advanced data preprocessing and feature selection
- Ensemble methods: Random Forest, Gradient Boosting
- Introduction to neural networks and deep learning
- Hyperparameter tuning and model optimization
- Working with large datasets and big data tools
Syllabus
Learning Outcome
- Develop more sophisticated machine learning models, optimize algorithms for better performance, and gain experience with neural networks and data management techniques.
Reviews
🛣️ Machine Learning Roadmap for Level 1 (Intermediate)
Advance your ML skills with real datasets, supervised learning, feature engineering, and essential libraries like Scikit-learn and XGBoost.
Machine Learning Level 01
Deepen your ML knowledge with advanced supervised and unsupervised learning, model evaluation, feature engineering, and ensemble methods.
Machine Learning Level 02
Master advanced ML algorithms, optimization techniques, and real-world applications in diverse domains.
Internship
Apply your ML skills on real projects during a free, 1-year internship to gain industry experience.
Mini Project
Solidify your knowledge with guided mini projects showcasing your machine learning expertise.
Expected Jobs
Prepare for roles like Senior ML Engineer, Data Scientist, AI Specialist, and ML Engineer.
🏆 Career Destinations
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