6. IOT
•Image/video
/audio/text
•Open source
•Proprietary
•Grabbed
Big data
• Artificial feature
extraction
• Statistics & Math
• Visual presentation
• Data Science
• Storage & Processing
Artificial
intelligence
• Logic
• Fuzzy
• ML
• DL
• xNN
Management
•Assistance
•Control
•Decision
•Design
Philosophy
•Benefit
•Regulation
•Creativity
Introduction to
Artificial Intelligence
(人工智慧概論)
Data Science
(資料科學)
Data Mining
(資料探勘)
Big Data
Analytics
(大數據分析)
Machine Learning
(機器學習)
Big Data Technology
and Administration
(大數據技術與管理)
Deep Learning
(深度學習)
Evidence-Based
Management
實證管理
Project Management
專案管理
Accounting & Finance
高階會計
國際金融
Decisions and
Strategy策略與決策
7. • 1. System View: Life , logic/system thinking: Interdisciplinary and multidisciplinary
• 1. Lab : Cloud setup , CMD ,CMD_function
• 2. Scientific System
• 2.1.Lab : Regex ,
• 3. System and signal/data/information : OO
• 3.1.Lab : Python Data type
• 4. System and Modeling
• 4. Lab : Sympy, Scipy, ODE
• 5. HI system :
• 5. Lab : Numpy, Panda, Visualization
• 6. Logic Calculus
• 6 .Lab : Prolog, Python condition and function, Data Collection and Parsing,
• 7. Linear algebra
• 7. Lab : Linear regression & Signal processing / transformation and processing
• 8. Statistics and probability and Implication, Sequential(Decision tree)
• 8. Lab : Decision Tree of ski-learn examples
• 9. Clustering, Classification, and strategy, Ensemble (Algorithm, game theory)
• 9. Lab : Decision Tree of ski-learn examples
23. Systems of science
Science
Empirical sciences
Formal science Natural science Social science
Foundation
• Logic
• Mathematics
• Statistics
• Physics
• Chemistry
• Biology
Earth science
• Astronomy
• Economics
• Political science
Sociology
• Psychology
Application • Computer science
• Engineering
• Agricultural science
Medicine
• Dentistry
• Pharmacy
• Business
administration
• Jurisprudence
• Education
https://en.wikipedia.org/wiki/Branches_of_science 分類 容易理解
24. Business Administration /
Management
• Management science (MS) is the broad interdisciplinary study of problem solving
and decision making in human organizations, with strong links
to management, economics, business, engineering, management consulting,
and other fields
25. What is system?
• A system is a group of interacting or interrelated
elements that act according to a set of rules to form
a unified whole.
• A system, surrounded and influenced by its
environment, is described by its
boundaries, structure and purpose and expressed in
its functioning.
26. Close or open system ?
• Boundary is beneficial for convergence.
29. Course Outline
• Lecture 1: System view
• Lecture 2: Scientific system
• Lecture 3: Signal and system
• Lecture 4: System and Modeling
• Lecture 5: Human intelligence
• Lecture 6: Logic Calculus
• Lecture 7: Mathematics and Python for system
S
Nature
S
Science
Material
IT
Social
HI
Complex
AI
32. Breadth and depth (深度與廣度)
System
Value
Unity
Relation
Model
Verification
Balance
Causality
Function
Upgrade
Nature/
Science
Re & Im
Physical quantity
Network
Math
Simulation
Equilibrium
Reasoning
Operation
Evolution
HI
訊/雜
人事時地物
介系詞關係
認知
推論
真假/是非
預測
分析/認知
決策
Logic
True/False
Fact
Rule
Logic
Check
Probability
Reasoning
Implication
Inference
IT
1/0
Data
Function
OO
Run
Benchmark
Condition
Algorithm
Optimization
47. Causality of sciences and systems
• Most of scientific systems are found
• Engineering systems are created.
48. Natural vs. Human-Made
Systems
• Races vs Racism
• Marine ecosystem vs supply chain ecosystem
• Human-Made system means the system is designed
• Design indicates the advantages of administration, prediction ,
management and optimization.
49. • Tensorflow
• pytorch
ML
• scikitlearn
Modeling
• Math: sympy
• Data :Scipy
Computing
• matplotlib
Data Visualization
• Numpy
• Pandas
Data Management
• Python
• Ipython/Jupyter
• Anaconda/conda
Data tools
數
學
Math
數
據
Data
np / array / matrix
df
plt
number / string / list / dict
ML, Regression
Solve
Optimization
Neural Network,
CNN, RNN
Build
model
from
data
50. List of available solutions
Data
Source
Data
Collection
/Ingestion
Stream
Data
Processing
Data
Storage
Data
Presentation
/Analysis
Communication
Protocol
Communication Data format:
JSON, CSV, BSON, YAML, XML
