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[General] DASCA SDS Exam Simulator Free, SDS Discount

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【General】 DASCA SDS Exam Simulator Free, SDS Discount

Posted at 10 hour before      View：12 | Replies：1        Print      Only Author   [Copy Link] 1#
BONUS!!! Download part of TestPDF SDS dumps for free: https://drive.google.com/open?id=1Rv2hf0JKpaho0vExqj6kYI1lQm632uHM
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Our online test engine and the windows software of the SDS study materials can evaluate your exercises of the virtual exam and practice exam intelligently. Our calculation system of the SDS study materials is designed subtly. Our evaluation process is absolutely correct. We are strictly in accordance with the detailed grading rules of the real exam. The point of every question is set separately. Once you submit your exercises of the SDS Study Materials, the calculation system will soon start to work.
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DASCA Senior Data Scientist Sample Questions (Q29-Q34):NEW QUESTION # 29
Which of the following is an example of NLP?
  • A. Finding which text documents are about similar topics
  • B. Using Twitter to assess public sentiment
  • C. All of the above
  • D. Both A and C
  • E. Flagging e-mails as spam
Answer: C
Explanation:
Natural Language Processing (NLP) is the field of machine learning that deals with human language understanding and generation. Applications include:
Option A (Spam detection): NLP techniques classify emails based on text patterns and context.
Option B (Sentiment analysis on Twitter): NLP models analyze textual data to extract emotions, opinions, and trends.
Option C (Topic modeling): NLP clustering and probabilistic models (e.g., LDA) classify documents by semantic similarity.
Since all are valid NLP applications, the correct answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Applications of Machine Learning: NLP in Real- World Use Cases.

NEW QUESTION # 30
Which of the following is the common evolutionary algorithm of neural networks?
  • A. Evolution strategy
  • B. All of the above
  • C. Genetic programming
  • D. Genetic algorithm
Answer: B
Explanation:
Evolutionary algorithms are optimization techniques inspired by natural selection. They are often applied in neural network optimization for evolving architectures, weights, or hyperparameters.
Genetic Algorithm (Option A): Uses selection, crossover, and mutation to evolve neural network parameters.
Genetic Programming (Option B): Evolves computer programs or expressions; can be applied to evolve neural network structures.
Evolution Strategy (Option C): Focuses on optimization using mutation and adaptation of parameters.
Since all are used as evolutionary approaches in neural networks, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Neural Networks: Evolutionary Algorithms in Machine Learning.

NEW QUESTION # 31
Which of the following is FALSE for Social Network Analysis (SNA)?
  • A. Social Network Analysis (SNA) is an example of trend analysis
  • B. Social Network Analysis (SNA) is an example of graph analysis
  • C. None of the above
  • D. SNA characterizes networked structures in terms of nodes and the ties or edges that connect them
  • E. SNA is used to investigate social structures and relationships across social networks
Answer: A
Explanation:
Social Network Analysis (SNA) is a powerful analytical method that applies graph theory to study relationships among entities (people, organizations, computers, etc.).
Option A: Correct. SNA is indeed an example of graph analysis because it models entities as nodes and their relationships as edges/ties.
Option B: FALSE. SNA is not an example of trend analysis. Trend analysis focuses on temporal patterns (time series), while SNA is structural and relational.
Option C: Correct. SNA investigates structures such as communities, influencers, and information diffusion in networks.
Option D: Correct. The characterization of nodes and edges is central to SNA.
Option E: Incorrect, since we've identified Option B as false.
Thus, the false statement is Option B.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Analytics: Graph Analysis & Social Network Analysis.

NEW QUESTION # 32
Which of the following is NOT an example of the applications of neural networks?
  • A. Character recognition
  • B. Stock market prediction
  • C. None of the above
  • D. Image compression
  • E. Traveling salesman's problem
Answer: E
Explanation:
Neural networks have been widely applied in various domains:
Option A (Character recognition): Correct application - neural networks are highly effective for OCR (Optical Character Recognition).
Option B (Stock market prediction): Correct application - neural networks are used to model time-series and nonlinear patterns in finance.
Option D (Image compression): Correct application - neural nets (autoencoders) are used for dimensionality reduction and compression.
Option C (Traveling salesman's problem): NOT a typical neural network application. This is a combinatorial optimization problem usually solved with heuristics, dynamic programming, or optimization algorithms (not standard neural networks).
Thus, the correct answer is Option C (Traveling salesman's problem).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Machine Learning Applications of Neural Networks.

NEW QUESTION # 33
What is Scrum?
  • A. Agile is a subset of Scrum
  • B. Scrum and Agile are the same
  • C. Scrum is a subset of Agile
  • D. None of the above
Answer: C
Explanation:
Scrum is a framework used to implement Agile principles. Agile itself is the overarching philosophy or mindset, while Scrum is one of the most popular frameworks that apply Agile values in practice.
Option A (Correct): Scrum is indeed a subset of Agile. Agile defines the principles (from the Agile Manifesto), and Scrum provides the structure (roles, artifacts, ceremonies).
Option B: Incorrect. Agile is broader and not a subset of Scrum.
Option C: Incorrect. Scrum and Agile are not the same; Agile is the philosophy, Scrum is a methodology under Agile.
Option D: Incorrect because Option A is valid.
Thus, the correct answer is Option A: Scrum is a subset of Agile.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Agile and Scrum in Data Science Projects.

NEW QUESTION # 34
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bobknig878

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Posted at 7 hour before        Only Author  2#
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