Hands-On One-shot Learning with Python

Challenges in machine learning and deep learning

Machine learning and deep learning have revolutionized the computer science industry, but they have advantages and disadvantages. Some of the common challenges faced by our current approaches are as follows:

• Data gathering: Collecting sufficient relevant data for each category for machines to learn is laborious.
• Data labeling: Often, labeling data requires experts or is impossible due to privacy, safety, or ethical issues.
• Hardware constraints: Due to the large amount of data, as well as large parametric models, expensive hardware (GPUs and TPUs) is required to train them.
• Result analysis: Understanding the result is also a major challenge, though there are certain open source libraries that ...