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ExplainX.ai is a fast, scalable and end-to-end Explainable AI framework for data scientists & machine learning engineers.
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With explainX, you can understand overall model behavior, get the reasoning behind model predictions, remove biases and create convincing explanations for your business stakeholders. [](https://twitter.com/intent/tweet?text=Explain%20any%20black-box%20Machine%20Learning%20model%20in%20just%20one%20line%20of%20code%21&url=https://www.explainx.ai&hashtags=xai,explainable_ai,explainable_machine_learning,trust_in_ai,transparent_ai)
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ExplainX.ai is a fast, light-weight and scalable Explainable AI framework for data scientists. It enables you to explain and debug state of the art machine learning models in as simple as one line of code. [](https://twitter.com/intent/tweet?text=Explain%20any%20black-box%20Machine%20Learning%20model%20in%20just%20one%20line%20of%20code%21&url=https://www.explainx.ai&hashtags=xai,explainable_ai,explainable_machine_learning,trust_in_ai,transparent_ai)
*[Provide Feedback to Improve explainX.ai](https://forms.gle/5Q1xaHd7s6UQkRzf8)
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## Installation on your laptop
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# Installation
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* You can use **explainX** on your own computer in under a minute.
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Python 3.5+ | Linux, Mac, Windows (Install [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) first to run on Windows.)
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* Make sure you have **Python 3.5+**
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```sh
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* Open the terminal and run the following to install **explainX**.
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```python
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pip install explainx
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```
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***Jupyter Notebook**: You can also install explainx via Jupyter Notebook. Just run the following command:
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```python
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!pip install explainx
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```
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## Installation on the cloud
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If you are using AWS SageMaker of Jupyter Notebook deployed on the cloud, visit our documentation for step-by-step guide installing and running explainX. [Cloud Installation Instructions](https://docs.explainx.ai/getting-started/installation)
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* Make sure you have **Python 3.5+**
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* Install **nodejs** and **localtunnel** using the following instructions.
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## Example Usage
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After successfully installing explainX, open up your Python IDE of Jupyter Notebook and simply follow the code below to use it:
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### To install **nodejs** and **localtunnel** on **MAC OS**
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* Open the terminal.
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* Install Xcode Command Line Tools using the following.
### To install **nodejs** and **localtunnel** on **Windows**
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* Install [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) found [here](https://visualstudio.microsoft.com/visual-cpp-build-tools/).
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* Install [Nodejs](https://nodejs.org/en/download/) found [here](https://nodejs.org/en/download/).
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* Open the terminal and run the following to install **localtunnel**.
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```python
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npm install -g localtunnel
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```
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1. Import **explainx**module.
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### Lastly, install **ExplainX**using the following.
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```python
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from explainx import*
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pip install explainx
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```
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2. Load and split your dataset into x_data and y_data
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***Jupyter Notebook**: You can also install explainx via Jupyter Notebook. Just run the following command:
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```python
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#x_data = Pandas DataFrame
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#y_data = Numpy Array or List
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!pip install explainx
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```
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## Usage
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Once you have install explainX, you can simply follow the example below to use it:
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x_data, y_data = explainx.dataset_boston()
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Import **explainx**
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```python
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from explainx import*
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```
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3. Train your model.
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Load dataset as X_Data, Y_Data in your XGBoost Model
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```python
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#X_Data = Pandas DataFrame
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#Y_Data = Numpy Array or List
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X_Data, Y_Data = explainx.dataset_boston()
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#Train Model
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model = xgboost.train({"learning_rate": 0.01}, xgboost.DMatrix(x_data, label=y_data), 100)
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model = xgboost.train({"learning_rate": 0.01}, xgboost.DMatrix(X_Data, label=Y_Data), 100)
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```
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4. Pass your model and dataset into the explainX function:
5.Click on the dashboard link to start exploring model behavior:
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Click on the link to view the dashboard.
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```python
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```jupyter
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App running on https://0.0.0.0:8080
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```
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**Running ExplainX on the cloud e.g., AWS Sagemaker?****https://0.0.0.0:8080** will not work. You would need to open the **terminal** and run the following command.
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**If you are running explainX on the cloud e.g., AWS Sagemaker?****https://0.0.0.0:8080** will not work.
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Please visit our documentation for installation instructions for the cloud: [Cloud Installation Instructions](https://docs.explainx.ai/getting-started/installation)
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After installation is complete, just open your **terminal** and run the following command.
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