WorksheetsData Science Fundamentals
Total questions: 25
Worksheet time: 50mins
Data Science…
uses machine learning algorithms to discover patterns in data that are not immediately apparent.
obtains meaningful insights and valuable information from data using statistical analysis, programming, and domain knowledge.
draws from the formal sciences including hypothesis creation and testing and formation of repeatable processes.
all of the above.
The purpose of data science is:
(select all that apply)
to analyze large amounts of structured or unstructured data to discover meaningful patterns.
to make evidence-based recommendations to improve a process or add value to a business.
to create a machine learning model as a goal for every project.
to better understand a dataset through exploratory data analysis including both data visualization and statistical tests.
to communicate the story of data to a target audience in a way that motivates action.
An (a) is a series of repeatable steps or rules used to accomplish specific data science tasks or solve a problem.
"_____________ _______________ is the science and art of programming computers so they can learn from data." -Aurélien Géron
(a)
What is the difference between Artificial Intelligence and Machine Learning?
(select all that apply)
Machine learning is a subset of artificial intelligence.
Artificial Intelligence is a branch of machine learning
Machine learning takes in a training data set to discover patterns and create algorithms that can be applied to future data to predict outcomes.
Artificial intelligence may not have the ability to learn or adjust based on new data but can mimic cognitive functions and perform difficult and repetitive tasks based on defined rules or algorithms.
Machine learning uses an algorithm to identify patterns from your training dataset that it can use to define parameters for a model that can then be used to make predictions on new data.
Unsupervised machine learning algorithms find connections between observations in a train dataset based only on features, without human input, and may go on to group observations based on their findings.
True
False
What are the four Vs of Data Big Data?
(select all that apply)
Viscosity
Volume
Variety
Velocity
Veracity
__________ _________ is data which does not fit a predefined data model. Often this data does not fit into the typical row-column structure of a database.
(a)
These configuration variables are internal to a model, so the values are estimated or learned from the data when the train dataset is being fit or trained. These are the parts of the model that are learned from historical training data.
Targets
Hyperparameters
Features
Parameters
Supervised machine learning algorithms train on data sets that include the labels or outcomes for each observation.
True
False
These are also known as the attributes, x variable(s), predictors, independent variables.
Targets
Hyperparameters
Features
Parameters
These configuration variables are external to a specific model. The values are not learned or estimated from data but adjusted manually when creating or tuning a model.
Targets
Hyperparameters
Features
Parameters
The (a) in a data set is also known as the label, the outcome, the dependent variable, the y variable, and the class.
__________ _________ is data which can fit into a predefined data model.
(a)
SQL, Structured Query Language, is a _________ _________ that allows you to communicate with databases.
RDBMS flavor
python library
computer language
visualization tool
___________ __________ file system, HDFS , allows for the distributed processing of large amounts of data across clusters of computers using simple programming models.
(a)
All of the following are data visualization tools except
Matplotlib
Spark
Seaborn
Tableau
Plotly
A (a) database, like Neo4j or Graphbase, is used primarily for analyzing social networks because of its efficiency at computing relationships of highly connected data.
TensorFlow and Keras are tools used for (a) learning.
All of the following are python libraries that are geared towards data science except
Pandas
NumPy
SciPy
D3.js
Statsmodels
A regression algorithm is used when your target is represented by a (a) variable.
A classification algorithm is used when your target is a (a) variable.
Anomaly Detection is the practice of identifying data points, items, observations or events that do not conform to the (a) pattern of a given group.
Time series analysis is about finding patterns in (a) data and making predictions, forecasting, based on those patterns.
__________ ________ _________, NLP, uses programming and machine learning techniques to help understand and make use of large amounts of text data.
(a)
