MLJ.jl
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Looking for a sequential progression of tutorials? See
DataScienceTutorials.jl
Data Processing
Classification
Regression
Clustering
Dimensionality Reduction
Neural Networks
Class Imbalance
Missing Value Imputation
Encoders
Feature Engineering
Hyperparameter Tuning
Pipelines
Iterative Models
Ensemble Models
Bayesian Models
Data Processing
Loading and Accessing Data
Manipulating Data Frames with DataFrames.jl
Working with Categorical Data
Understanding Scientific Types
Data Processing and Visualization
Vectors, Matrices and Data Loading in Julia
MLJ for Data Scientists in Two Hours
Linear Regression on Temporal Power Data
Classification
Preparing data and model with Iris
Supervised and Unsupervised Workflows in MLJ
Hyperparameter Tuning for Single and Composite Models
Logistic Regression & Friends on Stock Market Data
Exploring Tree-based Models
Building and Tuning a Support Vector Machine
MLJ for Data Scientists in Two Hours
KNN, Logistic Regression and PCA on Wine Dataset
XGBoost on Crabs Dataset
EvoTree Classifier on Horse Colic Dataset
Exploring Generalized Linear Models
Credit Fraud Detection with Classical and Deep Models
Benchmarking Classification Models on Breast Cancer Data
BMI Classification with Decision Trees
Effect of Ratios Oversampling Hyperparameter
From RandomOversampling to ROSE
SMOTE on Customer Churn Data
SMOTEN on Mushroom Data
SMOTENC on Customer Churn Data
Effect of ENN Hyperparameters
SMOTE-Tomek for Ethereum Fraud Detection
Balanced Bagging for Cerebral Stroke Prediction
Regression
Preparing data and model with Iris
Building and Tuning Bagging Ensemble Models
Building Random Forests with Bagging Ensembles
Composing Models and Target Transformations
Multivariate Linear Regression & Interactions
Building Polynomial Regression Models and Tuning Them
Ridge & Lasso Regression on Hitters Dataset
Exploring Tree-based Models
Tree-based models on King County Houses Dataset
Tree-based models on Airfoil Dataset
LightGBM on Boston Data
Exploring Generalized Linear Models
Linear Regression on Temporal Power Data
Custom Neural Networks on Boston Data
KNN & Ridge Regression Learning Network on AMES Pricing Data
Build Basic Learning Networks with MLJ
Clustering
Unsupervised Learning with PCA and Clustering
Dimensionality Reduction
Unsupervised Learning with PCA and Clustering
KNN, Logistic Regression and PCA on Wine Dataset
Neural Networks
Custom Neural Networks on Boston Data
Credit Fraud Detection with Classical and Deep Models
Benchmarking Classification Models on Breast Cancer Data
Class Imbalance
Credit Fraud Detection with Classical and Deep Models
BMI Classification with Decision Trees
Effect of Ratios Oversampling Hyperparameter
From RandomOversampling to ROSE
SMOTE on Customer Churn Data
SMOTEN on Mushroom Data
SMOTENC on Customer Churn Data
Effect of ENN Hyperparameters
SMOTE-Tomek for Ethereum Fraud Detection
Balanced Bagging for Cerebral Stroke Prediction
Missing Value Imputation
EvoTree Classifier on Horse Colic Dataset
Encoders
Supervised and Unsupervised Workflows in MLJ
Composing Models and Target Transformations
Ridge & Lasso Regression on Hitters Dataset
KNN, Logistic Regression and PCA on Wine Dataset
Tree-based models on Airfoil Dataset
Exploring Generalized Linear Models
Credit Fraud Detection with Classical and Deep Models
Benchmarking Classification Models on Breast Cancer Data
Feature Engineering
Building Polynomial Regression Models and Tuning Them
MLJ for Data Scientists in Two Hours
Hyperparameter Tuning
Hyperparameter Tuning for Single and Composite Models
Building and Tuning Bagging Ensemble Models
Building Random Forests with Bagging Ensembles
Building Polynomial Regression Models and Tuning Them
Ridge & Lasso Regression on Hitters Dataset
Exploring Tree-based Models
Building and Tuning a Support Vector Machine
XGBoost on Crabs Dataset
EvoTree Classifier on Horse Colic Dataset
Tree-based models on Airfoil Dataset
LightGBM on Boston Data
Custom Neural Networks on Boston Data
KNN & Ridge Regression Learning Network on AMES Pricing Data
Stacking with Learning Networks
Pipelines
Composing Models and Target Transformations
Unsupervised Learning with PCA and Clustering
MLJ for Data Scientists in Two Hours
KNN, Logistic Regression and PCA on Wine Dataset
EvoTree Classifier on Horse Colic Dataset
Exploring Generalized Linear Models
Credit Fraud Detection with Classical and Deep Models
SMOTE-Tomek for Ethereum Fraud Detection
Iterative Models
Exploring Tree-based Models
MLJ for Data Scientists in Two Hours
XGBoost on Crabs Dataset
EvoTree Classifier on Horse Colic Dataset
Tree-based models on King County Houses Dataset
LightGBM on Boston Data
Custom Neural Networks on Boston Data
Benchmarking Classification Models on Breast Cancer Data
BMI Classification with Decision Trees
Ensemble Models
Building and Tuning Bagging Ensemble Models
Building Random Forests with Bagging Ensembles
Stacking with Learning Networks
Bayesian Models
Logistic Regression & Friends on Stock Market Data
Benchmarking Classification Models on Breast Cancer Data