Data Science: Towards Data Scientist? ( AI Machine Learning - Data Science ) #datascience #machinelearning #ai

"What is Data Science?" with data science meaning and "What is data?" with data analytics may be initial questions possibly to start Data Science or Data Anaysis and possibly toward Data Scientist or Data Analyst. Besides, starting understanding on Python Data Science or Python Library (* Python is trademark of Python Software Foundation) may also be needed for possibly toward Data Scientist or Data Analyst. Data Science Engineering or Data Engineering may be one of success factors in the AI environment.

Would you like to manage to live in the AI environment?
Would you like to start Data Science?
Would you like to toward Data Scientist?

This Apps may possibly help the followings:
- understanding more on AI to manage to live in the AI environment
- possibly starting of Data Science
- possibly starting toward Data Scientist

This Apps may possibly with the following advantages:
- You may possibly find possibly find more fun with diagrammatic approach
- You may possibly find useful information for future reference where appropriately
- Single entity tights topics together in the Apps

Content of this Apps includes the followings:
1. Data science may mean simply?
2. Properties of data in data science
3. Type of data in data science
4. Where computing help data science possibly?
5. Where statistics help data science possibly?
6. Where machine learning/algorithm/model help data science possibly?
7. Where business domain help data science possibly?
8. What you may possibly get from data science?
9. How to possibly start approach data in Data Science? (Business Study)
10. How to possibly start approach data in Data Science? (Data Visualization)
11. How to possibly start approach data in Data Science? (Data Model Design)
12. How to possibly start preparing data in Data Science? (Data Preparation)
13. How to possibly start preparing data modelling in Data Science? (Data Modelling)
14. What is Machine Learning (ML)?
15. Relation between AI and Machine Learning (ML) possibly?
16. What is Deep Learning possibly?
17. What is methodology of machine learning possibly?
18. How to predict by model possibly?
19. How to predict by algorithm possibly?
20. What is Approach of Machine Learning possibly?
21. What is supervised learning possibly?
22. What is unsupervised learning possibly?
23. What is reinforcement learning possibly?
24. Relationship between model / algorithm and approach in ML possibly?
25. Relationship between model / algorithm and approach in ML possibly? (Example)
26. How to perform data modelling possibly?
27. How to perform data modelling possibly? (Data Modelling Library)
28. Can Python Library be considered for the model / algorithm?
29. What is Model Evaluation possibly?
30. What is Model Evaluation possibly? (Example of Evaluation Metrics)
31. What is Model Deployment possibly?
32. What is Process Flow of Model Deployment possibly?

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