ML_Tools

We connect (ML_Tools) with the Data Archive using Data-Archive-Link-Table. We have organised ML Tools into folders:

• Preprocess
• Build
• Selection
• Optimisation
• Deployment
• Observability

Table (Update-able)

Page	Link
ARIMA	Forecasting_AutoArima
ARIMA	ARIMA
Addressing Multicollinearity	Addressing_Multicollinearity
Anomaly Detection	Pycaret_Anomaly
Anomaly Detection in Time Series	TS_Anomaly_Detection
Binary Classification	Tutorial-BinaryClassification
Click	Click_Implementation
Clustering	Pycaret_Clustering
Cross Validation	KFold_Cross_Validation
DBSCAN	DBSCAN
Debugging	Debugging
Distributions	Distribution_Analysis
EDA	EDA_Pandas
Evaluation Metrics	Evaluation_Metrics
Gaussian Mixture Models	Gaussian_Mixture_Model_Implementation
Heatmap	Heatmaps_Dendrograms
Imbalanced Datasets	Imbalanced_Datasets_SMOTE
Imbalanced Datasets	Imbalanced_Data
Imbalanced Datasets	Imbalanced_Datasets_Resampling
K-means	KMeans
Logistic Regression	Regression_Logistic_Metrics
Model Ensemble	Comparing_Ensembles
One-hot encoding	One_hot_encoding
PCA-Based Anomaly Detection	PCA_Based_Anomaly_Detection
Precision-Recall Curve	ROC_PR_Example
Principal Component Analysis	PCA_Analysis
Prophet	prophet
Pydantic	Pydantic
Pytest	Testing_Pytest
ROC (Receiver Operating Characteristic)	ROC_curve
ROC (Receiver Operating Characteristic)	ROC_curve_kNN
Regularisation	Regularisation
Support Vector Machines	SVM_Example
Time Series	TS_Cross_Validation
Time Series	RandomForectRegForecaster
Time Series Forecasting	TS_Random_Forest
Vector Embedding	Vector_Embedding
Word2vec	Word2Vec
pdoc	pdoc_example