3) What are the various areas where AI (Artificial Intelligence) can be used?
Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics’s etc.
4 What methods are used for reducing dimensionality?
Dimensionality reduction is the process of reducing the number of random variables. We can reduce dimensionality using techniques such as missing values ratio, low variance filter, high correlation filter, random forest, principal component analysis, etc.
21) What is the function of the third component of the planning system?
In a planning system, the function of the third component is to detect when a solution to problem has been found.
5 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.
2 Differentiate between parametric and non-parametric models.
| Differentiation Based on | Parametric Model | Non-parametric Model |
| Features | A finite number of parameters to predict new data | Unbounded number of parameters |
| Algorithm | Logistic regression, linear discriminant analysis, perceptron, and Naive Bayes | K-nearest neighbors, decision trees like CART and C4.5, and support vector machines |
| Benefits | Simple, fast, and less data |
Flexibility, power, and performance |
| Limitations | Constrained, limited complexity, and poor fit | More data, slower, and overfitting |
34) What combines inductive methods with the power of first order representations?
Inductive logic programming combines inductive methods with the power of first order representations.
How does supervised machine learning work?
Supervised machine learning requires the data scientist to train the algorithm with both labeled inputs and desired outputs. Supervised learning algorithms are good for the following tasks:
Who’s using machine learning and what’s it used for?
Today, machine learning is used in a wide range of applications. Perhaps one of the most well-known examples of machine learning in action is the recommendation engine that powers Facebooks news feed.
Facebook uses machine learning to personalize how each members feed is delivered. If a member frequently stops to read a particular groups posts, the recommendation engine will start to show more of that groups activity earlier in the feed.
Behind the scenes, the engine is attempting to reinforce known patterns in the members online behavior. Should the member change patterns and fail to read posts from that group in the coming weeks, the news feed will adjust accordingly.
In addition to recommendation engines, other uses for machine learning include the following: