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Questions & Answers › Tag: Machine Learning
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What does the FID measure?
AnsweredGeek Boy asked 12 months ago • 
366 views1 answers0 votes
LLM Models are primarily used for _______________
AnsweredGeek Boy asked 12 months ago • 
420 views1 answers0 votes
Which metric is often used to evaluate the diversity of generated samples in generative AI models?
AnsweredGeek Boy asked 12 months ago • 
341 views1 answers0 votes
Which evaluation method involved measuring the difference between the model's output and human-generated output?
AnsweredGeek Boy asked 12 months ago • 
452 views1 answers0 votes
How do you measure the performance of a language model's ability to analyze prompts?
AnsweredGeek Boy asked 12 months ago • 
520 views1 answers0 votes
What does GAN's stand for in the context of generative AI?
AnsweredGeek Boy asked 12 months ago • 
423 views1 answers0 votes
What does an intrinsic evaluation measure in generative AI models?
AnsweredGeek Boy asked 12 months ago • 
377 views1 answers0 votes
A model developed by OpenAI that can generate images from textual descriptions.
AnsweredGeek Boy asked 12 months ago • 
387 views1 answers0 votes
What does BERT stand for?
AnsweredGeek Boy asked 12 months ago • 
360 views1 answers0 votes
OpenAI's language model specifically designed to generate creative texts like poetry __________
AnsweredGeek Boy asked 12 months ago • 
870 views1 answers0 votes
How do GAN's work?
AnsweredGeek Boy asked 12 months ago • 
417 views1 answers0 votes
What benefits does LangChain offer to developers?
AnsweredGeek Boy asked 12 months ago • 
398 views1 answers0 votes
What is the R function to apply hierarchical clustering to a matrix of distance objects?
AnsweredAdam asked 3 years ago • 
4292 views1 answers0 votes
What is the R Function to divide a dataset into k clusters?
AnsweredAdam asked 3 years ago • 
4695 views1 answers-1 votes
Members of the same cluster are far away / distant from each other.
AnsweredAdam asked 3 years ago • 
5583 views1 answers0 votes
_____________ is when points don't move between clusters and centroids stabilize.
AnsweredAdam asked 3 years ago • 
3727 views1 answers0 votes
K Means algorithm assumes Euclidean Space/Distance.
AnsweredAdam asked 3 years ago • 
5941 views1 answers0 votes
___________ is a way of finding the k value for k means clustering.
AnsweredAdam asked 3 years ago • 
6754 views1 answers0 votes
Hierarchical Clustering is a suggested approach for Large Data Sets.
AnsweredAdam asked 3 years ago • 
3240 views1 answers0 votes
Sampling is one technique to pick the initial k points in K Means Clustering.
AnsweredAdam asked 3 years ago • 
6263 views1 answers-1 votes
The number of rounds for convergence in k means clustering can be large.
AnsweredAdam asked 3 years ago • 
4774 views1 answers0 votes
A centroid is a valid point in a non-Euclidean space.
AnsweredAdam asked 3 years ago • 
5424 views1 answers0 votes
The ______ is a visual representation of how the data points are merged to form clusters.
AnsweredAdam asked 3 years ago • 
7566 views1 answers0 votes
___________ measures the goodness of a cluster.
AnsweredAdam asked 3 years ago • 
4074 views1 answers0 votes
___________ is the data point that is closest to the other point in the cluster.
AnsweredAdam asked 3 years ago • 
4156 views1 answers1 votes
What is the overall complexity of the the Agglomerative Hierarchical Clustering?
AnsweredAdam asked 3 years ago • 
5101 views1 answers0 votes
_____________ of a set of points is defined using a distance measure.
AnsweredAdam asked 3 years ago • 
7068 views1 answers1 votes
Which learning is the method of finding structure in the data without labels.
AnsweredAdam asked 3 years ago • 
3526 views1 answers0 votes
Unsupervised learning focuses on understanding the data and its underlying pattern.
AnsweredAdam asked 3 years ago • 
6553 views1 answers0 votes
What is a preferred distance measure while dealing with sets?
AnsweredAdam asked 3 years ago • 
7208 views1 answers0 votes
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