ML_crossword1

3. regression is a method of fitting a regression model by iteratively adding or removing variables.
5. learning is when the model is getting trained on a labelled dataset.
6. is a field of Artificial Intelligence (AI) that deals with the interaction between computers and human languages.
8. Artificial Network learning is robust to errors in the training data and has been successfully applied for learning real-valued, discrete-valued, and vector-valued functions containing problems such as interpreting visual scenes, speech recognition, and learning robot control strategies.
11. cleaning is a crucial step in the machine learning (ML) pipeline, as it involves identifying and removing any missing, duplicate, or irrelevant _____.
12. or a parse tree is a tree representation of different syntactic categories of a sentence. It helps us to understand the syntactical structure of a sentence.

1. Learning is the science of decision making. It is about learning the optimal behavior in an environment to obtain maximum reward.
2. If a feature represents a characteristic measured in numbers , it is called a _____ feature.
4. is a very popular python library for large multi-dimensional array and matrix processing.
7. data includes a label or target variable that the model is trying to predict, whereas unlabeled data does not include a label or target variable.
9. is a popular Python library for data analysis. It is not directly related to Machine Learning. As we know that the dataset must be prepared before training.
10. regression is a type of supervised machine learning algorithm that computes the linear relationship between a dependent variable and one or more independent features.