What is the need of cross validation in machine learning modeling? Cross validation is used to better utilize the input data to ensure the model performance. The input data will be divided into many subsets and train the machine learning model on all the subset except one among them. One subset will be kept as …
Differentiate between local optimization and global optimization Optimization is a process of assigning a set of inputs to an objective function that can extract the best possible output from the objective function. Local optimization tries to find extrema points, i.e., maxima or minima of the objective function in some specific or predefined region of the …
Explain label encoding and one hot encoding, Explain how the dimensionality of a dataset is affected with these methods in machine learning Machine learning algorithms can understand only numbers. Often, the dataset consists of categorical and numerical features. We need to convert the categorical features to numerical features for the machines to understand. This process …
Explain the concept confusion matrix in machine learning? Confusion matrix is a table displaying a summary of prediction results of a classification problem. Measuring accuracy of a model alone can be misleading in cases where the classification tasks involve more than one type of classes in the data set or the classification problem contains an …
Explain the terms Artificial Intelligence, Machine Learning, Deep Learning, and Reinforcement Learning? Artificial Intelligence (AI) is the domain of intelligent machines which can think rationally and act rationally. It uses algorithms to enable problem solving with robust dataset. Machine Learning (ML) and Deep Learning (DL) are subfields of artificial intelligence in which deep learning can …