Description
Curriculum
Instructor
Description:
Master Machine Learning from the ground up in this comprehensive course, perfect for intermediate to advanced learners. You’ll cover everything from fundamental algorithms to complex techniques used in AI-driven systems. Whether you’re looking to boost your career in tech, data science, or AI, this course provides a thorough understanding of Machine Learning concepts and real-world applications. With hands-on projects and practical coding exercises in Python and R, you’ll learn how to implement machine learning models and solve data challenges effectively.
Curriculum
- 20 Sections
- 0 Lessons
- Lifetime
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- Introduction to Machine Learning0 Items
- Supervised vs. Unsupervised Learning0 Items
- Data Preprocessing for Machine Learning0 Items
- Linear Regression Models0 Items
- Logistic Regression for Classification0 Items
- K-Nearest Neighbors (K-NN)0 Items
- Support Vector Machines (SVM)0 Items
- Decision Trees and Random Forests0 Items
- Naive Bayes Classifier0 Items
- K-Means Clustering0 Items
- Dimensionality Reduction (PCA)0 Items
- Neural Networks and Deep Learning0 Items
- Reinforcement Learning0 Items
- Model Evaluation and Cross-Validation0 Items
- Hyperparameter Tuning and Model Optimization0 Items
- Natural Language Processing (NLP) with Machine Learning0 Items
- AI with Deep Learning Frameworks (TensorFlow, PyTorch)0 Items
- Handling Imbalanced Datasets0 Items
- Real-World Machine Learning Applications0 Items
- Capstone Project: Building a Machine Learning System0 Items
Master Tutor
5 Students74 Courses
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