## Basic Introduction

Some Important Phases or fields
```
1. AI    :- Artificial Intelligence
2. ML    :- Machine Learning
3. DL    :- Deep Learning
4. DS    :- Data Science
```

Short Description of above different areas
![Areas](https://github.com/chavarera/PythonScript/blob/master/MachineLearning/img/field.png)

### 1. AI(Artificial Intelligence)
- Artificial intelligence is a branch of computer science that aims to create intelligent machines that enable machines to think like a normal human 
- Sometimes it also called machine intelligence.

#### Application of AI
```
- Image Recognition
- Chatbots
- Natural Language Generation
- Speech Recognition
- Sentimental Analysis
- Self Driving Cars
- Robotics
- Computer Vision
```
### 2. ML(Machine Learning)

- Machine Learning is the simple application of artificial intelligence that provides machines the ability to automatically learn and improve from experience without being
explicitly programmed.
- Machine learning is closely related to computational statistics, which focuses on making predictions using computers.
- Machine Learning enables machines or computer to make data-driven decisions rather than explicitly programming.

#### Types Of Machine Learning

1. Supervised Learning
2. Unsupervised Learning

#### Application of ML
```
- Social Media
- Fraud Detection
- Google Translate
- Medical Diagnosis
- Classifiers
- Stats Tool to learn from data
```

### 3. DL(Deep Learning)
- Deep Learning is the part of *Machine Learning* in *Artificial Intelligence*.
- Deep Learning also called as *Deep Neural Learning* or *Deep Neural Network*
- Deep Learning networks rely on layers of the ANN (artificial neural networks).

### Application Of DL
```
- Automatic speech recognition.
- Visual art processing.
- Customer relationship management.
- Recommendation systems.
```

### 4. DS(Data Science)
- Data Science is about Extraction, Preparation, Analysis, Visualization, and Maintenance of information
- Data Science is a completely different area than (AI, ML) But it Intersects all these areas.
- Understanding and Extraction of useful data is one function of Data science.

Applications OF DS
```
- Internet Search.
- Targeted Advertising.
- Visualization.
- Banking(Big Data and Data Science have enabled banks to keep up with the competition)
```


Python support following some important Libraries that are helpfull in (AI, ML, DL, DS)

```
Numpy
Pandas
Matplotlib
Scipy
Scikit-learn
Theano
TensorFlow
Keras
PyTorch
And Other Many More...
```