Related Issues (20)
- Incorporate "Pandas Library Support" ,for inputting the data HOT 1
- Implement Lasso regression a.k.a L1 Regularization HOT 2
- Implementing other "Anomaly Detection" Methods HOT 1
- Implementing other "Advanced Clustering / Unsupervised Learning" Models HOT 1
- Creative and Newer Format for "Algorithms / Domain" Detail Tables, in ReadMe HOT 1
- Implementing "Feature Scaling and Normalization Techniques" for Utility to Input Dataset HOT 1
- Implementing other "Optimized Gradient Descent Variants"
- Implement Complement Naive Bayes and Categorical Naive Bayes Models
- Implementing Optimizers
- Implement Linear Discriminant Analysis HOT 13
- Implement KNN Classifier HOT 2
- Add other Distance-based Cost Metrics into a Single Python Class File HOT 3
- Implement Bagging Classifier and Regressor
- Implement Decision Tree Regressor and Random Forest Regressor HOT 2
- Implement Hidden Markov Model
- Implement various Hypothesis Tests as Statistically Significant Metrics HOT 2
- Implement other types of Boosting Techniques
- Correction in Docstrings of Loss Functions
- Bug detected in Mean Squared Logarithmic Loss Function
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