Please enable JavaScript.
Coggle requires JavaScript to display documents.
Analytics (Types (Mid - High Complex Analytic Techniques (High Complexity…
Analytics
Types
Traditional Analytics
(Low Complexity - Less Likely to be adopted by AI)
Descriptive Statistics
Statistical Inference
Mid - High Complex Analytic Techniques
(High Complexity - More Likely to be adopted by AI)
Instance Based Learning
(Mid Complex)
Decision Tree Learning
(Mid Complex)
Regression Analysis
(High Complex)
Clustering
(High Complex)
Dark Data Analysis
(High Complex)
Sentiment Analysis
(High Complex)
Transfer Learning
(High Complex)
Reinforcement Learning
(High Complex)
Deep Learning
(High Complex)
AI
Deep Learning
Deep Learning Use Neural Networks
Are a subset of Machine Learning techniques
Are AI systems based on simulated connected units
(ie: Neurons interacting with the brain)
Systems that train large data sets using various inputs
(ie: images, video, speech)
Types of Neural Networks
Feed Forward Neural Networks
https://en.wikipedia.org/wiki/Feedforward_neural_network
First and simplest form of neural network conceived
Recurrent Neural Networks
https://en.wikipedia.org/wiki/Recurrent_neural_network
Ability to process sequences of inputs
Convolutional Neural Networks
https://en.wikipedia.org/wiki/Convolutional_neural_network
Used to analyze visual imagery
Focus
Map AI techniques to Problem Tyes
Use Case Insights
Analyze Industry to Analytic Types used
Quantify Potential Value of AI
Analyze market and quantify potential value of AI
Impact and Value
Analyze AI's impact to the organization
Document challenges in order to fast track AI adoption
Concerns
Issues with Bias
Data Security
Privacy