When we start building a deep learning model from scratch, it is hard to determine beforehand how many (different types of) layers we should stack. Generally, it is a good idea to have a look at a well-known deep learning model and use it as a basis to build further. In general, it is good to try to overfit to the training data as much as you can first. This ensures that your model is able to train on the input data. Afterwards, apply regularization techniques such as dropout to prevent overfitting and stimulate generalization.
United States
Great Britain
India
Germany
France
Canada
Russia
Spain
Brazil
Australia
Singapore
Hungary
Ukraine
Luxembourg
Estonia
Lithuania
South Korea
Turkey
Switzerland
Colombia
Taiwan
Chile
Norway
Ecuador
Indonesia
New Zealand
Cyprus
Denmark
Finland
Poland
Malta
Czechia
Austria
Sweden
Italy
Egypt
Belgium
Portugal
Slovenia
Ireland
Romania
Greece
Argentina
Netherlands
Bulgaria
Latvia
South Africa
Malaysia
Japan
Slovakia
Philippines
Mexico
Thailand