Machine Learning with Python by Cognitive Class
- Offered byCognitive Class
Machine Learning with Python by Cognitive Class at Cognitive Class Overview
Duration | 3 hours |
Mode of learning | Online |
Schedule type | Self paced |
Official Website | Go to Website |
Credential | Certificate |
Machine Learning with Python by Cognitive Class at Cognitive Class Course details
- Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction
- Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests
- This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language
- Learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each
Machine Learning with Python by Cognitive Class at Cognitive Class Curriculum
Supervised vs Unsupervised Learning
Machine Learning vs Statistical Modelling
Supervised vs Unsupervised Learning
Supervised Learning Classification
Unsupervised Learning
Supervised Learning I
K-Nearest Neighbors
Decision Trees
Random Forests
Reliability of Random Forests
Advantages & Disadvantages of Decision Trees
Supervised Learning II
Regression Algorithms
Model Evaluation
Model Evaluation: Overfitting & Underfitting
Understanding Different Evaluation Models
Unsupervised Learning
K-Means Clustering plus Advantages & Disadvantages
Hierarchical Clustering plus Advantages & Disadvantages
Measuring the Distances Between Clusters - Single Linkage Clustering
Measuring the Distances Between Clusters - Algorithms for Hierarchy Clustering
Density-Based Clustering
Dimensionality Reduction & Collaborative Filtering
Dimensionality Reduction: Feature Extraction & Selection
Collaborative Filtering & Its Challenges