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WorksheetsAI, Machine Learning, and Neural Networks
Total questions: 50
Worksheet time: 25mins
What is A.I?
Intelligence demonstrated by machines
Smart robots
Anthony Ian
I don't know
How does A.i work?
Combining large amounts of data with fast processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data.
The computation, mostly on computers, of antiderivatives and definite integrals in term of formulas
It just works you know??
Another super duper long answer to fool you guys to prove that not all longest answers are the correct ones, how is my quiz going anyway, i hope it is good, hope it is not too long though, thank you for not clicking
What is this?
artificial intelligence
algorithm
neural network
Which one of these is not an area of AI?
computer vision/image recognition
voice recognition
web design
robotics
How many images would you need of a cat, for example, to train a neural network ?
about 10
a few hundred
thousands
It is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed
Artificial Intelligence
Decision Tree
Machine Learning
Linear Regression
Which is the correct structure of a Neural Network?
Output, Hidden Layer, Input
Hidden Layer, Input, Output
Input, Hidden Layer, Output
This is where we insert the initial data for the neural network.
Input
Hidden Layer
Output
This is an intermediate layer between input and output layer and place where all the computation is done.
Input
Hidden Layer
Output
It produces the result for given inputs.
Input
Hidden Layer
Output
If we want to create a model of neural network that can identify whether you are wearing a mask or no, what is the ideal number of output that we should create?
1
2
3
What does lower latency mean?
Less time spent looking for networks
Faster Facebook scrolling
Less time for information to travel to and from your device
Enhanced computing performances
from the picture, what kind of programming is it?
Traditional Programming
Modern Programming
Machine Learning
Traditional Learning
from the picture, what kind of programming is it?
Traditional Programming
Machine Learning
Modern Programming
Traditional Learning
Which of the following is not type of learning?
Semi-unsupervised Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Targetted marketing, Recommended Systems, and Customer Segmentation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
This picture shows a result of ...
Supervised Learning: Classification
Unsupervised Learning: Regression
Unsupervised Learning: Prediction
Supervised Learning: Regression
What was Alan Turing's profession before he worked for the government?
Mechanic
Mathematician
Nurse
Teacher
What is the name of the test that Alan created to check whether something is human or a computer?
Test of Turing
Turner Test
Turing Machine
Turing Test
Turing's most famous post-war contribution was to the new field of ___
encryption
boolean logic
electromechanical computing
artificial intelligence
Turing postulated that a computer would deserve to be called intelligent if it could deceive ___
a human into believing that it was human
a computer into believing that it was human
a human into believing that it was a computer
a computer into believing that it was a computer
The method of determining whether or not a computer is capable of thinking like a human being is called ___
the Turing Test
the Enigma method
the Manchester analysis
CAPTCHA
The modern Turing test to tell computers and humans apart, is commonly abbreviated as ___
APTCHA
PACTCHA
CAPTCHA
CACPHAT
What do you call the feature that checks you are not a robot / hacking program?
Captcha
Proover
Tester
Grabber
What does CAPTCHA stand for?
Completely Automated Public Turing test to tell Computers and Humans Apart
Computers After Trying Can't Hack Algorithms
Comparing AI to People Tends to Create Headaches Always
Completely Arbitrary People Trying to Create Hacking Algorithms
Most advanced form of Artificial Intelligence is:
Deep Learning is the most advanced form of Artificial Intelligence.
Artificial Intelligence covers all the concepts and algorithms which, in some way or the other mimic human intelligence.
Machine learning is the most advanced form of Artificial Intelligence.
What 2 subjects are neural networks usually associated with?
Geology & CHemistry
Geology & Biology
Chemistry & Artificial-engineering
Biology & Artificial-engineering
What two types of Neural Networks are there
Biological Neural network and Artificial Neural Network
Chemical Neural Network and Biological Neural Network
Geological Neural Network and Artificial Neural Network
Chemical Neural Network and Geological Neural Network
No Free Lunch Theorem for Machine Learning (Wolpert, 1996) states that
No ML algorithm can solve unsolved problems
No ML algorithm can can be trained without supervision
No ML algorithm is better than any other across all possible datasets/problems
The more types of problems you want to solve the more work you need to put into your ML algorithm
It is impossible for ML algorithms to solve certain problems
Adding a new feature to the model always results in equal or better performance on the training set?
False
True
Which of the following methods do we use to find the best fit line for data in Linear Regression?
Least Square Error
Maximum Likelihood
Logarithmic Loss
Both A and B
_____ is a learning model that is used to identify a relationship between large amounts of information from a data set.
Classification
Multi class classification
Association
Unsupervised learning
The goal of clustering a set of data is to?
choose the best data from the set
divide them into groups of data that are near each other
determine the nearest neighbors of each of the data
predict the class of data
If the computer is trained to recognize cars, bikes and trucks with a human supervision.
Supervised Learning
Unsupervised Learning
The machine will group objects with similar features but will not be able to identify what this group label
Supervised Learning
Unsupervised Learning
Recommend a product based on your buying history
Supervised Learning
Unsupervised Learning
Identify Currency
Supervised Learning
Unsupervised Learning
Predict the price of a house
Supervised Learning
Unsupervised Learning
When the machine will be provided with features only. It will then try to group objects with similar features
Supervised Learning
Unsupervised Learning
learning from examples in a training data set is a
Supervised Learning
Unsupervised Learning
A set of instructions to follow in order to solve a problem...
Algorithm
Machine Learning
Neuron
Noural Network
A field in the dataset used in the machine learning algorithm. E.g. happy and sad
Dataset
unsupervised learning
supervised learning
Classifiers
All data is labeled and the algorithms learn to predict the output from the input data
Dataset
unsupervised learning
supervised learning
Classifiers
Several sets of data related to each other used to make decisions in machine learning algorithms. E.g. comments to make you happy and comments to make you sad
Dataset
unsupervised learning
supervised learning
Classifiers
The data is split according to a certain requirements
Decision tree learning
Predictive models
Reinforcement learning
sentiment analysis
What would make a robot intelligent?
It responds to the environment.
It calculates mathematical problems faster than human minds.
It responds to the environment according to previous experiences.
It can jump 1.5 meters higher than humans.
What is the difference between supervised and unsupervised machine learning?
In a supervised learning model, the algorithm learns on a labeled dataset, providing an answer key that the algorithm can use to evaluate its accuracy on training data. An unsupervised model, in contrast, provides unlabeled data that the algorithm tries to make sense of by extracting features and patterns on its own.
supervised learning model, the algorithm learns on a labeled dataset, providing an answer key that the algorithm can use to evaluate its accuracy on training data.
unsupervised model, in contrast, provides unlabeled data that the algorithm tries to make sense of by extracting features and patterns on its own.
All of Them
Exmples of Machine learning
All of Them
Speech to text
Google maps
Siri, Uber
What is the correct example of Supervised learning?
Face recognition
Speech Recognition
Netflix and YouTube recommendations
All of them
