# Untitled

In general, AI inspired by human like behavior  and intelligence, which mimicking natural capabilities (vision, speech, language processing, decision making and etc.. ). AI applications emulates these humanly characteristics.

Large volumes of data and inexpensive compute providing access to lot saas based AI applications

Data Science : Data Analysis and Processing, applying statistical methods and techniques  to explore hidden patterns, which helps to build models. \[ analyzing historical data]

* Extrapolating sample data to find trends and relationships
* Building models and hypothesis testing

Machine Learning: It is field of Data Science to develop, train and validate predictive models.

In nutshell, following are the stages, which is itaretive process till we statisfy with accuracy

* Data gathering
* Data preparation&#x20;
* Developing a model
* Training the model&#x20;
* exploring relationship among features in data
* Predict the outcome/labels



Challenges with AI:&#x20;

* Ethical concern
* Fairness
* Realiability
* Safety
* Privacy&#x20;
* Security
* Inclusiveness&#x20;
* Transparency
* Accountability



