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Can you list some disadvantages related to linear models? There are many disadvantages to using linear models, but the main ones are: Errors in linearity assumptions Lacks autocorrelation It can’t solve overfitting problems You can’t use it to calculate outcomes or binary outcomes In Inductive Logic Programming what needed to be satisfied? The objective of … Read more
List the steps involved in Machine Learning. Data collection Data preparation Choosing an appropriate model Training the dataset Evaluation Parameter tuning Predictions What steps would you take to evaluate the effectiveness of your ML model? You have to first split the data set into training and test sets. You also have the option of using … Read more
What’s the difference between inductive, deductive, and abductive learning? Inductive learning describes smart algorithms that learn from a set of instances to draw conclusions. In statistical ML, k-nearest neighbor and support vector machine are good examples of inductive learning. There are three literals in (top-down) inductive learning: Arithmetic literals Equality and inequality Predicates In deductive … Read more
What is a depth-first search algorithm? Depth-first search (DFS) is based on LIFO (last-in, first-out). A recursion is implemented with LIFO stack data structure. Thus, the nodes are in a different order than in BFS. The path is stored in each iteration from root to leaf nodes in a linear fashion with space requirement. How … Read more
What is TensorFlow? TensorFlow is an open-source Machine Learning library. It is a fast, flexible, and low-level toolkit for doing complex algorithms and offers users customizability to build experimental learning architectures and to work on them to produce desired outputs. Mention the difference between statistical AI and Classical AI ? Statistical AI is more concerned … Read more