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19. You want to create a machine learning algorithm to identify food recipes on the web. To do this, you create an algorithm that looks at different conditional probabilities. So if the post includes the word flour, it has a slightly stronger probability of being a recipe. If it contains both flour and sugar, it even more likely a recipe. What type of algorithm are you using?
40. Your data science team is working on a machine learning product that can act as an artificial opponent in video games. The team is using a machine learning algorithm that focuses on rewards: If the machine does some things well, then it improves the quality of the outcome. How would you describe this type of machine learning algorithm?
43. You work for a website that enables customers see all images of themselves on the internet by uploading one self-photo. Your data model uses 5 characteristics to match people to their foto: color, eye, gender, eyeglasses and facial hair. Your customers have been complaining that get tens of thousands of photos without them. What is the problem?
50. In 2015, Google created a machine learning system that could beat a human in the game of Go. This extremely complex game is thought to have more gameplay possibilities than there are atoms of the universe. The first version of the system won by observing hundreds of thousands of hours of human gameplay; the second version learned how to play by getting rewards while playing against itself. How would you describe this transition to different machine learning approaches?
52. In the HBO show Silicon Valley, one of the characters creates a mobile application called Not Hot Dog. It works by having the user take a photograph of food with their mobile device. Then the app says whether the food is a hot dog. To create the app, the software developer uploaded hundreds of thousands of pictures of hot dogs. How would you describe this type of machine learning?
59. You work for a large credit card processing company that wants to create targeted promotions for its customers. The data science team created a machine learning system that groups together customers who made similar purchases, and divides those customers based on customer loyalty. How would you describe this machine learning approach?
79. You work for a power company that owns hundreds of thousands of electric meters. These meters are connected to the internet and transmit energy usage data in real-time. Your supervisor asks you to direct project to use machine learning to analyze this usage data. Why are machine learning algorithms ideal in this scenario?
84. Your company wants to predict whether existing automotive insurance customers are more likely to buy homeowners insurance. It created a model to better predict the best customers contact about homeowners insurance, and the model had a low variance but high bias. What does that say about the data model?
86. You work for a music streaming service and want to use supervised machine learning to classify music into different genres. Your service has collected thousands of songs in each genre, and you used this as your training data. Now you pull out a small random subset of all the songs in your service. What is this subset called?
87. You work for an organization that sells a spam filtering service to large companies. Your organization wants to transition its product to use machine learning. It currently a list Of 250,00 keywords. If a message contains more than few of these keywords, then it is identified as spam. What would be one advantage of transitioning to machine learning?
88. You are part of data science team that is working for a national fast-food chain. You create a simple report that shows trend: Customers who visit the store more often and buy smaller meals spend more than customers who visit less frequently and buy larger meals. What is the most likely diagram that your team created?
What is machine learning with example?
Machine Learning is certainly a field with growing demand and interesting potential applications. If you're passionate about data and have strong analytical skills, then a career in machine learning could be very rewarding. There are many different types of jobs available in this field, so there's sure to be something that suits your skillset and interests.
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Why is machine learning used?
Machine learning is used because it can automatically detect patterns in data and then use those patterns to make predictions about new data. This is incredibly useful for tasks like identifying fraud, predicting consumer behavior, or even understanding natural language. So if any job seeker or candidate desires to learn more about Machine Learning then they should practice the given most important and the latest Machine Learning mcqs with answers.
What is machine learning in simple words?
A branch of artificial intelligence called machine learning is concerned with creating and researching systems that can learn from data. These algorithms can automatically improve given more data. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. We provide you with the best collection of Machine Learning multiple choice questions with answers to study and learn, which will make you the best scholar in this field.
What is the best programming language for machine learning?
The optimum language for machine learning does not exist. Different languages are better suited for different tasks. Many high-level languages are easy to learn and use, but they may not be the best choice for performance-critical applications such as machine learning. Quizack offers the most crucial and latest variety of Machine Learning multiple choice questions for all the candidates and job searchers who want to get the best results in their examinations and interviews.
Is machine learning a good career?
There is no doubt that machine learning is one of the hottest career choices right now. With the rapid expansion of artificial intelligence (AI) and its applications across industries, businesses are scrambling to hire experts in machine learning to help them automate processes and make better decisions. If you want to make your career superior then first you have to get the basic knowledge about the topic, so for this purpose, we give you the important Machine Learning MCQ questions to study. It will help you build up your skill abilities.