1. Investment banks can use AI in six critical ways
Natural Language Processing (NLP) is a common notion for a variety of Machine Learning methods that make it possible for the computer to understand and perform operations using human (i.e. natural) language as it is spoken or written.
2. Reinforcement learning
Reinforcement Learning differs in its approach from the approaches we’ve described earlier. In RL the algorithm plays a “game”, in which it aims to maximize the reward. The algorithm tries different approaches “moves” using trial-and-error and sees which one boost the most profit.
All the data that is used for either building or testing the ML model is called a dataset. Basically, data scientists divide their datasets into three separate groups:
- Training data is used to train a model. It means that ML model sees that data and learns to detect patterns or determine which features are most important during prediction.
- Validation data is used for tuning model parameters and comparing different models in order to determine the best ones. The validation data should be different from the training data, and should not be used in the training phase. Otherwise, the model would overfit, and poorly generalize to the new (production) data.