Main Challenges of Machine Learning
Jun 6, 2021
In short, since your main task is to select a learning algorithm and train it on some data, the two things that can go wrong are “bad algorithm” and “bad data.” Let’s start with examples of bad data.
- Insufficient Quantity of Training Data
- Non-representative Training Data
- Poor-Quality Data
- Irrelevant Features
Bad Algorithm:
- Overfitting the Training Data
- Underfitting the Training Data
