Deep learning is just a subset of machine learning. It technically is machine learning and functions in a similar way (hence why the terms are sometimes loosely interchanged), but its capabilities are different.
Basic machine learning models do become progressively better at whatever their function is, but they still some guidance. If an ML algorithm returns an inaccurate prediction, then an engineer needs to step in and make adjustments. But with a deep learning model, the algorithms can determine on their own if a prediction is accurate or not.
A deep learning model is designed to continually analyze data with a logic structure similar to how a human would draw conclusions. To achieve this, deep learning uses a layered structure of algorithms called an artificial neural network (ANN). The design of an ANN is inspired by the biological neural network of the human brain. This makes for machine intelligence that’s far more capable than that of standard machine learning models.
- Cross selling/Recommendation algorithms
- Customer Segmentation/ Lead Prioritization
- Demand / Sales Forecasting
- Machine Learning – Sentiment Analysis
- Recency Frequency Monetary Analysis