Hands-On Transfer Learning with Python

Data retrieval

Data collection and extraction is where the story usually begins. Datasets come in all forms including structured and unstructured data that often includes missing or noisy data. Each data type and format needs special mechanisms for data handling as well as management. For instance, if a project concerns analysis of tweets, we need to work with Twitter APIs and develop mechanisms to extract the required tweets, which are usually in JSON format.

Other scenarios may involve already existing structured or unstructured public datasets or private ones, both may require additional permissions apart from just developing extraction mechanisms. A fairly detailed account pertaining to working with diverse data formats is discussed in ...