> For the complete documentation index, see [llms.txt](https://maheshwarappa-a.gitbook.io/explainable-ai-1/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://maheshwarappa-a.gitbook.io/explainable-ai-1/contents.md).

# Contents

1. [`What is Explainable AI?`](/explainable-ai-1/what-is-explainable-ai.md)
2. [`Why do we need Expalainbility?`](/explainable-ai-1/why-do-we-need-explainablity.md)
3. [`Explainable Systems and Black Box Systems`](/explainable-ai-1/explainable-systems-and-black-box-systems.md)
4. [`Types of Explainability Techniques`](/explainable-ai-1/types-of-model-interpretability.md)
5. [`Explainable Models`](/explainable-ai-1/interpretable-machine-learning-models.md)
   1. [`Linear Regression`](/explainable-ai-1/interpretable-machine-learning-models/linear-regression.md)
      1. [`Introduction`](/explainable-ai-1/interpretable-machine-learning-models/linear-regression.md)
      2. [`Assumptions`](/explainable-ai-1/interpretable-machine-learning-models/linear-regression/assumptions.md)
      3. [`Model`](/explainable-ai-1/interpretable-machine-learning-models/linear-regression/model-1.md)
      4. [`Statistical interpretation`](/explainable-ai-1/interpretable-machine-learning-models/linear-regression/model.md)
   2. [`Decision Trees`](/explainable-ai-1/interpretable-machine-learning-models/decision-trees.md)
      1. [`Introduction`](/explainable-ai-1/interpretable-machine-learning-models/decision-trees.md)
      2. [`How Do They Work?`](/explainable-ai-1/interpretable-machine-learning-models/decision-trees/how-do-they-work.md)
      3. [`Creating the model`](/explainable-ai-1/interpretable-machine-learning-models/decision-trees/creating-the-model.md)
      4. [`Interpretation`](/explainable-ai-1/interpretable-machine-learning-models/decision-trees/interpretation.md)
6. [Model Agonistic Methods](/explainable-ai-1/model-agonistic-methods.md)
   1. [SHapley Additive exPlanations](/explainable-ai-1/model-agonistic-methods/shap.md)
   2. [Surrogate model](/explainable-ai-1/model-agonistic-methods/surrogate-model.md)
   3. [Local Interpretable Model-Agnostic Explanations and  K-LIME](/explainable-ai-1/model-agonistic-methods/lime-and-k-lime.md)
   4. [Partial Dependence Plot](/explainable-ai-1/model-agonistic-methods/pdp.md)
   5. [Individual Conditional Plots](/explainable-ai-1/model-agonistic-methods/ice.md)
7. [Data sets](/explainable-ai-1/datasets.md)
   1. [Medical cost personal Dataset](/explainable-ai-1/datasets/medical-cost-personal-dataset.md)
   2. [Telecom Churn Dataset](/explainable-ai-1/datasets/telecom-churn-dataset.md)
   3. [Sales Opportunity Size Dataset](/explainable-ai-1/datasets/sales-opportunity-size-dataset.md)
   4. [Pima Indians Diabetes Datasets](/explainable-ai-1/datasets/pima-indians-diabetes-dataset.md) 
8. [Implementation of these techniques on different models](/explainable-ai-1/implementation-of-these-techniques-on-different-models.md)
   1. [Logistic regression](/explainable-ai-1/implementation-of-these-techniques-on-different-models/logistic-regression.md)
   2. [Random forest ](/explainable-ai-1/implementation-of-these-techniques-on-different-models/untitled.md)
   3. [GBM - PDP](/explainable-ai-1/implementation-of-these-techniques-on-different-models/gbm-pdp.md)
   4. [GBM - ICE](/explainable-ai-1/implementation-of-these-techniques-on-different-models/gbm-ice.md)  
   5. [Deep Learning](/explainable-ai-1/implementation-of-these-techniques-on-different-models/deep-learning-surrogate.md)


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