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Questions & Answers › Tag: Machine Learning
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What does the FID measure?
AnsweredGeek Boy asked 1 year ago • 
432 views1 answers0 votes
LLM Models are primarily used for _______________
AnsweredGeek Boy asked 1 year ago • 
480 views1 answers0 votes
Which metric is often used to evaluate the diversity of generated samples in generative AI models?
AnsweredGeek Boy asked 1 year ago • 
398 views1 answers0 votes
Which evaluation method involved measuring the difference between the model's output and human-generated output?
AnsweredGeek Boy asked 1 year ago • 
518 views1 answers0 votes
How do you measure the performance of a language model's ability to analyze prompts?
AnsweredGeek Boy asked 1 year ago • 
616 views1 answers0 votes
What does GAN's stand for in the context of generative AI?
AnsweredGeek Boy asked 1 year ago • 
489 views1 answers0 votes
What does an intrinsic evaluation measure in generative AI models?
AnsweredGeek Boy asked 1 year ago • 
413 views1 answers0 votes
A model developed by OpenAI that can generate images from textual descriptions.
AnsweredGeek Boy asked 1 year ago • 
443 views1 answers0 votes
What does BERT stand for?
AnsweredGeek Boy asked 1 year ago • 
408 views1 answers0 votes
OpenAI's language model specifically designed to generate creative texts like poetry __________
AnsweredGeek Boy asked 1 year ago • 
1412 views1 answers0 votes
How do GAN's work?
AnsweredGeek Boy asked 1 year ago • 
481 views1 answers0 votes
What benefits does LangChain offer to developers?
AnsweredGeek Boy asked 1 year ago • 
478 views1 answers0 votes
What is the R function to apply hierarchical clustering to a matrix of distance objects?
AnsweredAdam asked 3 years ago • 
4329 views1 answers0 votes
What is the R Function to divide a dataset into k clusters?
AnsweredAdam asked 3 years ago • 
4753 views1 answers-1 votes
Members of the same cluster are far away / distant from each other.
AnsweredAdam asked 3 years ago • 
5607 views1 answers0 votes
_____________ is when points don't move between clusters and centroids stabilize.
AnsweredAdam asked 3 years ago • 
3763 views1 answers0 votes
K Means algorithm assumes Euclidean Space/Distance.
AnsweredAdam asked 3 years ago • 
5994 views1 answers0 votes
___________ is a way of finding the k value for k means clustering.
AnsweredAdam asked 3 years ago • 
6790 views1 answers0 votes
Hierarchical Clustering is a suggested approach for Large Data Sets.
AnsweredAdam asked 3 years ago • 
3257 views1 answers0 votes
Sampling is one technique to pick the initial k points in K Means Clustering.
AnsweredAdam asked 3 years ago • 
6290 views1 answers-1 votes
The number of rounds for convergence in k means clustering can be large.
AnsweredAdam asked 3 years ago • 
4798 views1 answers0 votes
A centroid is a valid point in a non-Euclidean space.
AnsweredAdam asked 3 years ago • 
5458 views1 answers0 votes
The ______ is a visual representation of how the data points are merged to form clusters.
AnsweredAdam asked 3 years ago • 
7612 views1 answers0 votes
___________ measures the goodness of a cluster.
AnsweredAdam asked 3 years ago • 
4103 views1 answers0 votes
___________ is the data point that is closest to the other point in the cluster.
AnsweredAdam asked 3 years ago • 
4191 views1 answers1 votes
What is the overall complexity of the the Agglomerative Hierarchical Clustering?
AnsweredAdam asked 3 years ago • 
5154 views1 answers0 votes
_____________ of a set of points is defined using a distance measure.
AnsweredAdam asked 3 years ago • 
7099 views1 answers1 votes
Which learning is the method of finding structure in the data without labels.
AnsweredAdam asked 3 years ago • 
3552 views1 answers0 votes
Unsupervised learning focuses on understanding the data and its underlying pattern.
AnsweredAdam asked 3 years ago • 
6582 views1 answers0 votes
What is a preferred distance measure while dealing with sets?
AnsweredAdam asked 3 years ago • 
7256 views1 answers0 votes
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