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https://github.com/waseemofficial/python-and-scikit-learn
Python and Scikit-Learn
https://github.com/waseemofficial/python-and-scikit-learn
Last synced: 22 days ago
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Python and Scikit-Learn
- Host: GitHub
- URL: https://github.com/waseemofficial/python-and-scikit-learn
- Owner: waseemofficial
- Created: 2024-02-04T12:56:27.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-03-07T08:40:17.000Z (8 months ago)
- Last Synced: 2024-10-11T03:03:46.895Z (about 1 month ago)
- Language: Jupyter Notebook
- Size: 38.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
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### Languages
### Technologies
# **Machine Learning using Scikit-Learn**
- Data Cleaning
- missing values
- outliers
- imputing
- data type conversion
- data imbalance detection
- classifing data into catogrical and numerical
- Data Pre-Processing
- Standardization
- Normalization
- One-Hot Encoding
- Label Encoding
- Dummy Data Encoding
- Feature Engineering
- mlxtend
- SequentialFeatureSelector
- Sequential Backward Selection (SBS)
- Sequential Forward Selection (SBS)
- Feature Importance Permutation
- Feature Scaling
- Feature Selection
- Feature Extraction
- Feature Transformation
- Explotri Data Analysis (EDA)
- univariate analysis
- Bivariate analysis
- Multivariate Analysis
- Pandas-profiling
- Model Selection
- Type of Data
- image and video -> oprncv Convolution Nural Network(CNN)
- text data or Speach -> (RNN)
- Numerical data -> SVM,Logistic Regression,Decision Tree etc
- Based on the Task we need to carry out
- Classification task -> SVM,Logistic Regression,Decision Tree etc
- Regression Task -> Linear Regression,Random Forest,Polynomial Regression etc
- Clustering Task -> K-Means Cluster,Hierarchical Clustering (**Unsupervised Learning**)
- Model Buld
- Decision Tree
- Random Forest
- Linear Regression
- Mean Absolute Error(MAE),Mean Squired Error(MSE), Root Mean Squired Error(RMSE), R2 Score (Coefficent of Determination), Adjusted R2 Score
- Gradient Descent (optimization technique)
- Logistic Regression
- Gradient Descent (optimization technique)
- Support Vector Machie (SVM)
- Naive Bayes
- K-Nearest Neighbors (KNN)
- K-Means Cluster
- Evaluation
- Hyperparameter Tuning
- GridSearchCV
- RandomizedSearchCV
- Accuracy Score
- Confusion Matrix
- Precision
- Recall
- F1 Score
- Ensemble Learning
- Voting Ensemble
- Bagging Ensemble
- Boosting Ensemble
- Ada-Boosting
- Gradient Boosting
- XGBoost
- Stacking Ensemble