# alimuhammad78/machine-learning-complete-journey architecture

> Architecture diagram of the GitHub repository alimuhammad78/machine-learning-complete-journey, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-29). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/alimuhammad78/machine-learning-complete-journey
- Repository: https://github.com/alimuhammad78/machine-learning-complete-journey

## Overview

This repository is a machine-learning study collection, not a packaged runtime application. Its principal learning workflow moves from preparing data through supervised modeling, evaluation, and model improvement; separate branches hold coursework and reference material. The README documents these topics and their intended workflow, but no source excerpts were provided, so the graph represents documented learning relationships rather than verified notebook execution or function calls.

Main entry points: [`Supervised/all_models.ipynb`](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/all_models.ipynb) (Supervised overview), [`data_preprocessing`](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/data_preprocessing) (Preprocessing techniques), [`data_preprocessing/titanic_complete.csv`](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/data_preprocessing/titanic_complete.csv) (Titanic dataset), [`Supervised/Regression`](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/Regression) (Regression models)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_prep["Data preparation"]
  node_dataset["Titanic dataset"]
  node_prep_notebooks["Preprocessing techniques"]
end

subgraph group_supervised["Supervised learning"]
  node_supervised_overview["Supervised overview<br/>[all_models.ipynb]"]
  node_regression["Regression models"]
  node_regression_metrics["Regression metrics"]
  node_classification["Classification models"]
  node_classification_algorithms["Classification algorithms"]
  node_ensembles["Ensemble learning"]
end

subgraph group_improve["Evaluation and improvement"]
  node_evaluation["Model evaluation"]
  node_tuning["Hyperparameter tuning"]
  node_best_model["Best model selection"]
  node_pipelines["ML pipelines"]
  node_improvement["Model improvement"]
end

subgraph group_learning["Coursework and references"]
  node_assignments["Course assignments"]
  node_slides["Course slides"]
  node_advanced_topics["Advanced topics"]
end

node_learner(("Learner"))

node_learner -->|"studies data"| node_dataset
node_learner -->|"studies preparation"| node_prep_notebooks
node_dataset -->|"prepares data"| node_prep_notebooks
node_learner -->|"studies models"| node_supervised_overview
node_prep_notebooks -->|"prepares for"| node_supervised_overview
node_supervised_overview -->|"covers regression"| node_regression
node_supervised_overview -->|"covers classification"| node_classification
node_classification -->|"covers algorithms"| node_classification_algorithms
node_classification_algorithms -->|"includes ensembles"| node_ensembles
node_regression -->|"evaluates regression"| node_regression_metrics
node_supervised_overview -->|"covers evaluation"| node_evaluation
node_evaluation -->|"informs tuning"| node_tuning
node_tuning -->|"supports selection"| node_best_model
node_best_model -->|"supports workflow"| node_pipelines
node_regression_metrics -->|"informs improvement"| node_improvement
node_learner -->|"completes coursework"| node_assignments
node_learner -->|"studies references"| node_slides
node_slides -->|"covers topics"| node_advanced_topics

click node_dataset "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/data_preprocessing/titanic_complete.csv"
click node_prep_notebooks "https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/data_preprocessing"
click node_supervised_overview "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/all_models.ipynb"
click node_regression "https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/Regression"
click node_regression_metrics "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/Regression/Regression_Evaluation_metrics.ipynb"
click node_classification "https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/Classification"
click node_classification_algorithms "https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/common"
click node_ensembles "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Bagging_And_Boosting_Algorithm.ipynb"
click node_evaluation "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Cross_Validation.ipynb"
click node_tuning "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/HyperParameter_Tuning.ipynb"
click node_best_model "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Best_Model_With_Hyperparameter_Tuning.ipynb"
click node_pipelines "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Machine_Learning_Pipeline.ipynb"
click node_improvement "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/Regression/Model_Improvement_Techniques.ipynb"
click node_assignments "https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Assignments"
click node_slides "https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/slides"
click node_advanced_topics "https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/slides/010-Embeddings-SequenceModels-Transformers-Complete-v4.0.pdf"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_dataset,node_prep_notebooks toneBlue
class node_supervised_overview,node_regression,node_regression_metrics,node_classification,node_classification_algorithms,node_ensembles toneAmber
class node_evaluation,node_tuning,node_best_model,node_pipelines,node_improvement toneMint
class node_assignments,node_slides,node_advanced_topics toneRose
class node_learner toneIndigo
```

## Components

### Data preparation

- [Titanic dataset](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/data_preprocessing/titanic_complete.csv): `data_preprocessing/titanic_complete.csv`
- [Preprocessing techniques](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/data_preprocessing): `data_preprocessing`

### Supervised learning

- [Supervised overview](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/all_models.ipynb): `Supervised/all_models.ipynb`
- [Regression models](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/Regression): `Supervised/Regression`
- [Regression metrics](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/Regression/Regression_Evaluation_metrics.ipynb): `Supervised/Regression/Regression_Evaluation_metrics.ipynb`
- [Classification models](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/Classification): `Supervised/Classification`
- [Classification algorithms](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Supervised/common): `Supervised/common`
- [Ensemble learning](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Bagging_And_Boosting_Algorithm.ipynb): `Supervised/common/Bagging_And_Boosting_Algorithm.ipynb`

### Evaluation and improvement

- [Model evaluation](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Cross_Validation.ipynb): `Supervised/common/Cross_Validation.ipynb`
- [Hyperparameter tuning](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/HyperParameter_Tuning.ipynb): `Supervised/common/HyperParameter_Tuning.ipynb`
- [Best model selection](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Best_Model_With_Hyperparameter_Tuning.ipynb): `Supervised/common/Best_Model_With_Hyperparameter_Tuning.ipynb`
- [ML pipelines](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/common/Machine_Learning_Pipeline.ipynb): `Supervised/common/Machine_Learning_Pipeline.ipynb`
- [Model improvement](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/Supervised/Regression/Model_Improvement_Techniques.ipynb): `Supervised/Regression/Model_Improvement_Techniques.ipynb`

### Coursework and references

- [Course assignments](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/Assignments): `Assignments`
- [Course slides](https://github.com/alimuhammad78/machine-learning-complete-journey/tree/main/slides): `slides`
- [Advanced topics](https://github.com/alimuhammad78/machine-learning-complete-journey/blob/main/slides/010-Embeddings-SequenceModels-Transformers-Complete-v4.0.pdf): `slides/010-Embeddings-SequenceModels-Transformers-Complete-v4.0.pdf`

### Other components

- **Learner**

## Connections

- Learner → Titanic dataset: studies data
- Learner → Preprocessing techniques: studies preparation
- Titanic dataset → Preprocessing techniques: prepares data
- Learner → Supervised overview: studies models
- Preprocessing techniques → Supervised overview: prepares for
- Supervised overview → Regression models: covers regression
- Supervised overview → Classification models: covers classification
- Classification models → Classification algorithms: covers algorithms
- Classification algorithms → Ensemble learning: includes ensembles
- Regression models → Regression metrics: evaluates regression
- Supervised overview → Model evaluation: covers evaluation
- Model evaluation → Hyperparameter tuning: informs tuning
- Hyperparameter tuning → Best model selection: supports selection
- Best model selection → ML pipelines: supports workflow
- Regression metrics → Model improvement: informs improvement
- Learner → Course assignments: completes coursework
- Learner → Course slides: studies references
- Course slides → Advanced topics: covers topics