Relationship between AI, Machine Learning and Deep Learning

AI

Artificial Intelligence Tripleism

Symbolicism

Knowledge Map

NLP

Evolutionism / Cyberneticsism

Reinforcement Learning

Automation Control

Connectionism

Neural Networks

2 Low tide or 3 high tide

  • Perceptron, 1950s, High
  • Linear perceptron function is limited, 1968, Low
  • Back-propagation Algorithm, 1986, High
  • SVM Algorithm, 1995, Low
  • Multilayer neural network structure with AutoEncoder, 2006, High

Machine Learning = Algorithm + Neural Networks

Let the machine behave like the intelligent behavior that people show.

ID3 Decision tree algorithm, 1986

Regression & Clustering -> VC Dimension

SVM & RandomForest

Three Modes of Machine Learning

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Machine Learning Directions

Machine Learning Scientist

Research Machine Learning Algorithm

Machine Learning Engineering

Apply Machine Learning Algorithm to current business.

Machine Learning Platform

Build and Maintain Distributed Machine Learning Platform

Deep Learning = AutoEncoder + Multilayer neural network structure

Data Mining vs Machine Learning

machine-learning-vs-data-mining

Machine Learning -> CTR Prediction algorithm

Data Mining -> Mining new characteristics in data

Searching Engine

Machine Learning is relatively less important.

Crawler Sub-system

Information Index Sub-system

Association Rules

NLP, Computer Visual and Sound Recognization

Big Data vs Machine Learning

4V

Volume

Velocity

Variety

Value

3 Factors

Hadoop is created based on it, and Spark is based on it.

Google FS

MapReduce

Bigtable

Data Analysis

Focus in human’s subjective initiative to analysis the data.

A funny history roadmap of Hadoop

History

mindmap

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