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Overview
This foundational course introduces the core concepts of machine learning using Python. It covers key algorithms including linear regression, decision trees, clustering, and classification. Learners get hands-on experience with popular Python libraries like scikit-learn to preprocess data, train models, and evaluate performance. The course emphasizes understanding when and how to apply different machine learning techniques effectively. Real-world datasets and projects help solidify knowledge, making this course ideal for beginners seeking to enter the field of machine learning or enhance their...
Syllabus
- Mean, Median and Mode
- Standard Deviation
- Percentiles
- Data Distribution
- Normal Data Distribution
- Scatter Plot
- Linear Regression
- Polynomial Regression
- Multiple Regression
- Scale
- Train or Test data
- Decision Tree
- Confusion Matrix
- Hierarchical Clustering
- Logistic Regression
- Grid Search
- Categorical Data
- K-Means
- Bootstrap Aggregation
- Cross Validation
- AUC-ROC Curve
- K-nearest neighbors
Instructor
Sara Academy
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