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Unsupervised Learning
Q.
What is Dimensionality Reduction?
Q.
When to use PCA vs Random Projection?
Q.
What is Random Projection? Discuss its advantages and disadvantages?
Q.
How does T-SNE compare to PCA?
Q.
How does T-distributed Stochastic Neighbor Embedding (T-SNE) work at a high level?
Q.
What is Factor Analysis, and how does it differ from PCA?
Q.
What is Independent Component Analysis (ICA), and how is it distinguished from PCA?
Q.
What is Kernel PCA?
Q.
What is Principal Component Analysis (PCA), and how does it differ from clustering?
Q.
Pros and Cons of Gaussian Mixture Models (GMM) Clustering
Q.
How does the EM algorithm (in the context of GMM) compare to K-Means?
Q.
What are some options for identifying the number of components in a GMM?
Q.
What is a Gaussian Mixture Model (GMM)?
Q.
What is Expectation-Maximization (EM)?
Q.
What is Spectral co-clustering?
Q.
What is Bi-Clustering? What are possible use cases of it?
Q.
What is Spectral Clustering?
Q.
How does DBSCAN Clustering work, and in what cases is it useful?
Q.
How is clustering affected by high-dimensional data, and how can the quality of clusters generated be improved in such cases?
Q.
What are some options for clustering on categorical data? What if the dataset contains a combination of numeric and categorical features?
Q.
What are some of the pros and cons of hierarchical clustering compared to K-Means?
Q.
What is a dendrogram, and how is it used in hierarchical clustering?
Q.
How does imposing connectivity constraints help with Agglomerative clustering?
Q.
What are some of the possible linkage types to use in order to form successive clusters?
Q.
What are the two ways in which Hierarchical clustering can proceed?
Q.
What are the Pros and Cons of K-Means Clustering?
Q.
How do outliers affect the clusters formed in K-Means?
Q.
How does K-Means ++ work?
Q.
What is the effect of minimizing the within-cluster sum of squares on the shapes of clusters produced in K-Means?
Q.
What loss function does K-Means seek to minimize?
Q.
How does the initial choice of centroids affect the K-Means algorithm?
Q.
How can you choose the optimal value for ‘k’ in K-Means?
Q.
How does K-Means Work?
Q.
What is KL Divergence?
Q.
What is Jaccard Index / Distance?
Q.
What is Cosine Similarity?
Q.
What is Minkowski Distance?
Q.
What is Manhattan Distance?
Q.
What is Mahalanobis Distance?
Q.
What is Euclidean Distance?
Q.
What are some common distance metrics that can be used in clustering?
Q.
What is Mutual Information (MI)?
Q.
What is Adjusted Rand Index (ARI)?
Q.
What is Rand Index?
Q.
What is Dunn Index?
Q.
What is Silhouette Score?
Q.
What is Within Cluster Sum of Squares (WCSS)?
Q.
What are some common evaluation metrics in clustering?
Q.
What is Model-based Clustering?
Q.
What is Hierarchical Clustering?
Q.
What is Probabilistic (Fuzzy) Clustering?
Q.
What is Exclusive Clustering?
Q.
What are the most common categories of clustering?
Q.
What is Clustering?
Q.
What is Unsupervised learning?
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Explore Questions by Topics
Computer Vision
(1)
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Data Preparation
(35)
Feature Engineering
(30)
Sampling Techniques
(5)
–
Deep Learning
(52)
–
DL Architectures
(17)
Feedforward Network / MLP
(2)
Sequence models
(6)
Transformers
(9)
DL Basics
(16)
DL Training and Optimization
(17)
Generative AI
(2)
Machine Learning Basics
(18)
–
Natural Language Processing
(27)
NLP Data Preparation
(18)
Statistics
(34)
–
Supervised Learning
(115)
–
Classification
(70)
Classification Evaluations
(9)
Ensemble Learning
(24)
Logistic Regression
(10)
Other Classification Models
(9)
Support Vector Machine
(9)
–
Regression
(41)
Generalized Linear Models
(9)
Linear Regression
(26)
Regularization
(6)
–
Unsupervised Learning
(55)
–
Clustering
(37)
Clustering Evaluations
(6)
Distance Measures
(9)
Gaussian Mixture Models
(5)
Hierarchical Clustering
(3)
K-Means Clustering
(9)
Dimensionality Reduction
(9)
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