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DASCA Senior Data Scientist Sample Questions (Q54-Q59):
NEW QUESTION # 54
What is TRUE for "rehashing"?
- A. Both A and B
- B. Allocate a new, larger hash table in memory
- C. It requires a new hash function, which maps values into a larger range of integers
- D. Key/value pairs from the original table can be inserted into the new, larger one
- E. All of the above
Answer: E
Explanation:
Rehashing is a technique used in dynamic hash tables when the load factor (ratio of entries to bucket size) exceeds a certain threshold. It ensures efficient lookup, insertion, and deletion operations.
Option A (Correct): A larger hash table is allocated in memory to accommodate more entries.
Option B (Correct): A new hash function is typically required to map keys into the expanded table range.
Option C (Correct): All key-value pairs from the old table are re-inserted (rehashed) into the new table using the new hash function.
Since all three conditions (A, B, and C) are true, the best choice is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Data Structures & Hashing Techniques
NEW QUESTION # 55
Which of the following is correct?
i. LaTeX is used to publish work in a scientific journal
ii. LaTeX is a markup language that can be compiled into formatted documents iii. LaTeX is for publishing scientific papers
- A. i, iii
- B. i, ii
- C. ii, iii
- D. i, ii, iii
Answer: D
Explanation:
LaTeX is a high-quality typesetting system widely used in academia, particularly in scientific publishing.
Statement i: Correct. LaTeX is widely used to prepare manuscripts for scientific journals, theses, and technical reports.
Statement ii: Correct. LaTeX is a markup language (similar to HTML in concept) that compiles into formatted PDFs/documents.
Statement iii: Correct. LaTeX is a standard for publishing scientific papers due to its ability to handle complex mathematical equations, references, and formatting.
Thus, all three statements are true # Option B (i, ii, iii).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming Tools for Data Science: LaTeX for Scientific Documentation.
NEW QUESTION # 56
What is DevOps?
- A. All
- B. Software Development
- C. Quality Assurance
- D. Software Operations
Answer: A
Explanation:
DevOps is not just about coding (development) or system administration (operations). It is a holistic cultural and technical practice that unifies:
Software Development (Option A): Writing and building applications.
Software Operations (Option B): Deploying, monitoring, and maintaining systems in production.
Quality Assurance (Option C): Ensuring the reliability, security, and performance of applications through testing and automation.
Thus, DevOps encompasses all three dimensions, making the correct answer Option D (All).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Applications of Data Science: DevOps & Continuous Delivery.
NEW QUESTION # 57
Which of the following is NOT Structured data?
- A. Data tables
- B. XML
- C. None of the above
- D. CSV files
- E. Relational databases
Answer: B
Explanation:
Structured data refers to highly organized data stored in predefined formats such as rows and columns.
Relational databases (Option A): Structured.
Data tables (Option B): Structured.
CSV files (Option C): Structured because they are tabular with rows and columns.
XML (Option D): Not structured but semi-structured because it stores hierarchical information with tags and attributes.
Thus, the correct answer is Option D (XML).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Big Data Fundamentals: Structured vs Semi- structured Data.
NEW QUESTION # 58
Which of the following is main Machine Learning Library in Python?
- A. Scikit-learn
- B. SciPy
- C. None of the above
- D. Matplotlib
- E. NumPy
Answer: A
Explanation:
Python supports multiple libraries for scientific computing and data analysis, but the primary machine learning library is:
Scikit-learn (Option B): Provides a wide range of machine learning algorithms for classification, regression, clustering, model evaluation, and preprocessing. It is the core ML library in Python.
NumPy (Option A): Provides numerical computing and array operations, essential for ML but not a machine learning library itself.
Matplotlib (Option C): Used for data visualization.
SciPy (Option D): Supports scientific computing and numerical methods, not focused on ML models.
Therefore, the correct answer is Option B (Scikit-learn).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Python Libraries for Machine Learning.
NEW QUESTION # 59
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