https://techcrunch.com/2017/04/13/neural-networks-made-easy/

University of Michigan - Ann Arbor

A helpful website that introduces neural networks:
https://missinglink.ai/guides/neural-network-concepts/

Neural Network Reference

Neural network made easy

Pros: They can effectively capture complex features given enough data and computation.
Cons: The training time, data and customization is significant if the model is large and complex. Data need to be carefully preprocessed to be used as input. 

Pros and Cons of Neural Networks

Depends greatly on the nature of the target task and domain, the availability of in-domain labels, the latency and capacity constraints of the applications, and so on. Has 5 steps.

How to choose the best neural network model for my task.

+ New Datasets for More Challenging Tasks
+ Modeling Commonsense Knowledge
+ Interpretable DL Models
+ Memory Efficient Models
+ Few-Shot and Zero-Shot Learning

Challenges and opportunities

5 main methods: Accuracy and Error Rate; Precision / Recall / F1 score; Exact Match (EM); Mean Reciprocal Rank (MRR)

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