https://github.com/analyticalnahid/supervised-machine-learning
Most popular supervised Machine Learning algorithms from scratch with Scikit-learn implementation
https://github.com/analyticalnahid/supervised-machine-learning
machine-learning machine-learning-algorithms supervised-classification-methods supervised-learning supervised-learning-algorithms supervised-machine-learning
Last synced: about 2 months ago
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Most popular supervised Machine Learning algorithms from scratch with Scikit-learn implementation
- Host: GitHub
- URL: https://github.com/analyticalnahid/supervised-machine-learning
- Owner: analyticalnahid
- License: mit
- Created: 2022-08-26T16:34:52.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2022-08-31T14:10:33.000Z (over 2 years ago)
- Last Synced: 2025-02-02T12:37:33.928Z (4 months ago)
- Topics: machine-learning, machine-learning-algorithms, supervised-classification-methods, supervised-learning, supervised-learning-algorithms, supervised-machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 28.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Supervised-Machine-Learning
Most popular supervised Machine Learning algorithms from scratch with Scikit-learn implementation.
## 1. Linear Regression
#### 1.1 Simple Linear
#### 2.2 Regression Regression Metrics
#### 2.3 Multiple Linear Regression
#### 2.4 Gradient Descent
1. Batch Gradient Descent
2. Stochastic Gradient Descent
3. Mini batch Gradient Descent
#### 2.5 Polynomial Regreession
#### 2.5 Regularized Linear Regreession
1. Ridge
2. Lasso
3. Elastic Net
## 2. Logistic Regression
#### 2.1 Binary Classification
#### 2.2 Classification Metrics
#### 2.3 Multiclass Classification
#### 2.4 Polynomial Regreession
## 3. Support Vector Machine
#### 3.1 Support Vector Regressor
1. Linear SVR
2. Non-linear SVR (Kernel Trcik)
#### 3.2 Support Vector Classifier
1. Linear SVC
2. Non-linear SVC (Kernel Trcik)
## 4. Naive Bayes
1. Multinomial Naive Bayes
2. Gaussian Naive Bayes
3. Bernoulli Naive Bayes
## 5. K Nearest Neighbors
1. KNN Classifier
2. KNN Regressor
## 6. Decision Trees
1. Decision Tree Classifier
2. Decision Tree Regressor
## 8. Ensemble Learning
8.1 Voting Ensemble
1. Voting Classifier
2. Voting Regressor
8.2 Bagging Ensemble
1. Bagging Classifer
2. Bagging Regressor
3. Random Forest
8.3. Boosting
1. Adaptive Boosting
2. Gradient Boosting
3. Xtreme Gradient Boosting
4. Stacking and Blending
## 🔗 Links
Connect with me:
