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BasicIntroduction.md

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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

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...