GitHub - thomaskty/Data-Science-Knowledge-Base: A curated collection of machine learning, deep learning, and statistics resources. Includes Jupyter notebooks with notes, lab experiments, research explorations, and practical examples—perfect for learning, reference, and experimentation.

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A curated collection of machine learning, deep learning, and statistics resources. Includes Jupyter notebooks with notes, lab experiments, research explorations, and practical examples—perfect for learning, reference, and experimentation.

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Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
.ipynb_checkpoints		.ipynb_checkpoints
data		data
leetcode150		leetcode150
.DS_Store		.DS_Store
00000_Coding Questions.ipynb		00000_Coding Questions.ipynb
0000_General Notes.ipynb		0000_General Notes.ipynb
000_Linear Regression.ipynb		000_Linear Regression.ipynb
001_Logistic Regression.ipynb		001_Logistic Regression.ipynb
002_Time Series Analysis.ipynb		002_Time Series Analysis.ipynb
003_data analysis using pandas.ipynb		003_data analysis using pandas.ipynb
004_Recommendation System.ipynb		004_Recommendation System.ipynb
005_Numpy operations.ipynb		005_Numpy operations.ipynb
006_KNN Algorithm.ipynb		006_KNN Algorithm.ipynb
007_Naive Bayes.ipynb		007_Naive Bayes.ipynb
008_Support Vector Machines.ipynb		008_Support Vector Machines.ipynb
009_Bias Variance Tradeoff.ipynb		009_Bias Variance Tradeoff.ipynb
010_Decision Trees.ipynb		010_Decision Trees.ipynb
011_Ensemble Methods.ipynb		011_Ensemble Methods.ipynb
012_Cluster Evaluation Metrics.ipynb		012_Cluster Evaluation Metrics.ipynb
013_Regression Evaluation Metrics.ipynb		013_Regression Evaluation Metrics.ipynb
014_Classification Evaluation Metrics.ipynb		014_Classification Evaluation Metrics.ipynb
015_Random Forest.ipynb		015_Random Forest.ipynb
016_Kmeans Clustering.ipynb		016_Kmeans Clustering.ipynb
017_Adaboost Algorithm.ipynb		017_Adaboost Algorithm.ipynb
018_Gradient Boosting.ipynb		018_Gradient Boosting.ipynb
019_XGBoost Algorithm.ipynb		019_XGBoost Algorithm.ipynb
020_CatBoost_LGBM.ipynb		020_CatBoost_LGBM.ipynb
021_DBSCAN.ipynb		021_DBSCAN.ipynb
022_Hierarchical Clustering.ipynb		022_Hierarchical Clustering.ipynb
023_Model Calibration.ipynb		023_Model Calibration.ipynb
024_Feature Selection Methods.ipynb		024_Feature Selection Methods.ipynb
025_Feature Importance.ipynb		025_Feature Importance.ipynb
026_PCA.ipynb		026_PCA.ipynb
027_Deep Learning Basics.ipynb		027_Deep Learning Basics.ipynb
028_Population Stability Index.ipynb		028_Population Stability Index.ipynb
029_Information Theory Topics.ipynb		029_Information Theory Topics.ipynb
030_Case Studies.ipynb		030_Case Studies.ipynb
PT000_Neural Network.ipynb		PT000_Neural Network.ipynb