Deep Learning
[Neuroscience ](https://texonom.com/neuroscience-b45d9f638a2b4330906556c402307925) 


### Neural Network based Machine Learning method
composition of differentiable functions
Brain Algorithm + [Neural Network](https://texonom.com/neural-network-86f54f9f1de848c1a29c56c24f7d5094)  + [Big Data](https://texonom.com/big-data-236ec9f0ed844f4d8a5ca3236dfa442c) 
limit - explainability, fairness, generalizability, causality
Main feature of neural network It can find non-heuristic feature representation
### Deep Learning Notion
|Title|
|:-:|
|[Deep Learning Math](https://texonom.com/deep-learning-math-57c204edef3042568bbd0d5268b877fd)|
|[Deep Learning Network](https://texonom.com/deep-learning-network-f368faf8fa634699aeda503d01c193f0)|
|[End-to-end Deep Learning](https://texonom.com/end-to-end-deep-learning-16bd62f447a144f1b251acf25f1f8789)|



### Deep Learning Usages
|Title|
|:-:|
|[Deep Learning Tool](https://texonom.com/deep-learning-tool-a14ea6f4574342ef974443634e27c6ce)|
|[Deep Learning Compiler](https://texonom.com/deep-learning-compiler-7d79af9683764b6b983793c1856578c6)|
|[Sentiment Neuron](https://texonom.com/sentiment-neuron-2e44e9754b894534af6c121b6d6074d6)|
|[Learn Deep Learning](https://texonom.com/learn-deep-learning-4382083fb54d4705984e7f45a9af2d86)|



### Interview from popular people
> [제프리 힌턴이 말하는 AI의 영향력과 잠재력](https://www.youtube.com/watch?v=IvUw9um4Bv8)

> [OpenAI의 핵심, Ilya Sutskever 인터뷰](https://www.youtube.com/watch?v=SGCFeIbpGlU&t=722s)





