# The content of Data science and Deep learning
## Deep learning
- [Concept](/8yHR-4LAQ4mqYnlKJZUqMg)
- [Computational Graph](/2ytOCBRrRdSt9Rx7pkDWDw)
## statistic
### Basic
- [Introduction to Data](/DCx4G18NQ5uEXVkrJTkPAQ)
- [Introduction to Probability](/lGbjt-2aQk6o6gKIXsZe6A)
- [Type-1 and Type-2 error](https://hackmd.io/hYcO1tAHRKyX-nKWWpIE7Q)
- [The Chi-Squared Test](/StOM1LZiSIivJavXvQ51sg)
### Bayes' theorem
- [Bayes' theorem](/sWO7I6VlQUeoybX85PG14w?view)
### Regression
- [Regression](/oTmB7lvAT4KNrowqA84WHQ)
- [Logistic regression](/NbodF9C_QyesMvnOnvdPqA)
### Foundations for inference
- [Inference](/iwKtXyoyTgGKQ0RlUtpZqQ)
### Machine Learning
- [Ensemble learning](/gcU03FJYQSaTtPbi8q8bxg)
### Diagnostic
- [Diagnostic model](/EUICpdVkQYuKLgP2QqvoVQ)

### Sample
- [Sample](/oyP294krQ2a712k6ElQM_A)

## Application
- [Intelligent factory](/RKY7jA-gR-qgR7Gz0KG_cQ)
- [Factory 3.5](/LhFZpdYPSuaT5E0it0-EGg)

## Python Note
- [FASTAPI](/U0cu-Y0hQqyHfCxFicdMhw)
- [How deep of analysis](/GyEaEHcCQBecIfpip6A6sA)

## System Design
- [SystemDesign001](MpgJpAgZQ4ar461t_HqB1Q?both=)