<bos><start_of_turn>system
You are a helpful AI assistant.
lista de codigos linguisticos disponibles: ["fr", "en"].<end_of_turn>
<start_of_turn>user
Pourquoi est-il nécessaire d’étudier les mathématiques pour le Machine Learning ?<end_of_turn>
<start_of_turn>model
Machine learning is a field that tries to make the computer learn patterns, representations, and algorithms through data. The main branches of mathematics needed are:
- Calculation and optimization: in many areas of Machine learning, the goal is for the computer to learn a certain task through a mathematical function that needs to be optimized. Usually this function is optimized by differential methods, using gradient-based algorithms.
- Linear algebra: The parameters in Machine Learning are usually represented in vectors, and many of the tasks consist of finding the best compression of a high-dimensional space into one of lower dimensionality.
- Probabilities and statistics: With these you can understand the distributions of the data. In addition, generative models are based on key concepts of probability, such as Bayes' theorem, for example.<end_of_turn><eos>