# Recent questions tagged machine

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How does machine learning work?
How does machine learning work?How does machine learning work? ...
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What is the difference between uplift modelling and traditional machine learning?
What is the difference between uplift modelling and traditional machine learning?What is the difference between uplift modelling and traditional machine learning? ...
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How might advertising with no apparent informational content in fact convey information to consumers?
How might advertising with no apparent informational content in fact convey information to consumers?How might advertising with no apparent informational content in fact convey information to consumers? ...
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What are the main challenges of machine learning?
What are the main challenges of machine learning?What are the main challenges of machine learning? ...
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What are the goals of learning analytics?
What are the goals of learning analytics?What are the goals of learning analytics? ...
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Why should a machine learning model be good at discrimination?
Why should a machine learning model be good at discrimination?Why should a machine learning model be good at discrimination? ...
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A consumer durable company is planning to launch a new type of washing machine. The company would like to have information about how consumers select a brand of washing machine.A consumer durable company is planning to launch a new type of washing machine. The company would like to have information about how consumers select ...
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A machine having an efficiency of 50% does 500 joules of work. Which of the following is the work input? Is it:
A machine having an efficiency of 50% does 500 joules of work. Which of the following is the work input? Is it:A machine having an efficiency of 50% does 500 joules of work. Which of the following is the work input? Is it: w) 500 joules x) 250 joules y) 1000 ...
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A machine's output is 4000 joules and its frictional losses are 1000 joules. Which of the following is its efficiency? Is it:
A machine's output is 4000 joules and its frictional losses are 1000 joules. Which of the following is its efficiency? Is it:A machine's output is 4000 joules and its frictional losses are 1000 joules. Which of the following is its efficiency? Is it: w) 25% x) 30% y) 75% ...
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A car is moving along a straight horizontal road at a speed of 20 meters per second. The brakes are applied and a constant force of 5000 Newtons decelerates the car to a stop in 10 seconds. The mass of the car is:A car is moving along a straight horizontal road at a speed of 20 meters per second. The brakes are applied and a constant force of 5000 Newtons decel ...
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A machine performs 8 Joules of work in 2 seconds. How much power is delivered by this machine?
A machine performs 8 Joules of work in 2 seconds. How much power is delivered by this machine?A machine performs 8 Joules of work in 2 seconds. How much power is delivered by this machine? ...
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A certain machine exerts a force of 200 newtons on a box whose mass is 30 kilograms. The machine moves the box a distance of 20 meters along a horizontal floor. What amount of work does the machine do on the box?A certain machine exerts a force of 200 newtons on a box whose mass is 30 kilograms. The machine moves the box a distance of 20 meters along a horizon ...
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When is an angle said to be in standard position?
When is an angle said to be in standard position?When is an angle said to be in standard position? ...
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What are the shortcomings of machine learning?
What are the shortcomings of machine learning?What are the shortcomings of machine learning? ...
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What are some of the low and high-bias Machine Learning algorithms?
What are some of the low and high-bias Machine Learning algorithms?What are some of the low and high-bias Machine Learning algorithms? ...
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What are the steps in a data analysis process?
What are the steps in a data analysis process?What are the steps in a data analysis process? ...
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What are the steps in the data science process?
What are the steps in the data science process?What are the steps in the data science process? ...
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What is the mathematical representation of the idea behind the machine learning workflow?
What is the mathematical representation of the idea behind the machine learning workflow?What is the mathematical representation of the idea behind the machine learning workflow? ...
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What is structure of the optimisation problem in mathematics and machine learning?
What is structure of the optimisation problem in mathematics and machine learning?What is structure of the optimisation &nbsp;problem in mathematics and machine learning? ...
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What are the most common abbreviations and acronyms in machine learning and data science?
What are the most common abbreviations and acronyms in machine learning and data science?What are the most common abbreviations and acronyms in machine learning and data science? ...
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A machine is said to be a third class lever when the
A machine is said to be a third class lever when theA machine is said to be a third class lever when the (a) load is between the fulcrụm and effort (b) fulcrum is between the effort and load. (c) eff ...
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A machine is programmed to cut lengths of string from a uniform string coming up continuously from a factory belt.
A machine is programmed to cut lengths of string from a uniform string coming up continuously from a factory belt.A machine is programmed to cut lengths of string from a uniform string coming up continuously from a factory belt. The lengths are all measured in met ...
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What are the steps in the Machine Learning Problem Framing process?
What are the steps in the Machine Learning Problem Framing process?What are the steps in the Machine Learning Problem Framing process? ...
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What steps are part of the machine learning pipeline?
What steps are part of the machine learning pipeline?What steps are part of the machine learning pipeline? ...
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The probability of sample space is
The probability of sample space isThe probability of sample space is ...
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Is a perturbation machine essentially a causal inference machine because it can literally take the actions that are not possible in real life?
Is a perturbation machine essentially a causal inference machine because it can literally take the actions that are not possible in real life?Is a perturbation machine essentially a causal inference machine because it can literally take the actions that are not possible in real life? ...
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So counterfactual is considered a disjoint set of CATE, rather than a subset?
So counterfactual is considered a disjoint set of CATE, rather than a subset?So counterfactual is considered a disjoint set of CATE, rather than a subset? ...
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What are quartiles?
What are quartiles?What are quartiles? ...
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How can we avoid overfitting in decision tree learning?
How can we avoid overfitting in decision tree learning?How can we avoid overfitting in decision tree learning? ...
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How can we build never-ending machine learners?
How can we build never-ending machine learners?How can we build never-ending machine learners? ...
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What kinds of machine learning tools are needed to understand sentences?
What kinds of machine learning tools are needed to understand sentences?What kinds of machine learning tools are needed to understand sentences? ...
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How can we develop parallel, low-communication machine learning algorithms?
How can we develop parallel, low-communication machine learning algorithms?How can we develop parallel, low-communication machine learning algorithms? ...
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How can we use machine learning for biological and medical research?
How can we use machine learning for biological and medical research?How can we use machine learning for biological and medical research? ...
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What are the primary machine learning algorithms?
What are the primary machine learning algorithms?What are the primary machine learning algorithms? ...
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What are some fields where machine learning is already the preferred approach?
What are some fields where machine learning is already the preferred approach?What are some fields where machine learning is already the preferred approach? ...
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5 things to consider when deploying ML into production
5 things to consider when deploying ML into production5 things to consider when deploying ML into production ...
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What is the 5-step Machine Learning (ML) meta algorithm?
What is the 5-step Machine Learning (ML) meta algorithm?What is the 5-step Machine Learning (ML) meta algorithm? ...
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If discrimination is the objective of machine learning models, then why are activists fighting for fair algorithms?
If discrimination is the objective of machine learning models, then why are activists fighting for fair algorithms? If discrimination is the objective of machine learning models, then why are activists fighting for fair algorithms? Example: Binary logistic regres ...
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What is an algorithm?
What is an algorithm?What is an algorithm? ...
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Which Machine Learning algorithm does not require dealing with missing value?
Which Machine Learning algorithm does not require dealing with missing value?Which Machine Learning algorithm does not require dealing with missing value? ...
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What proportion of the points in a hypercube of dimension 50 are in the boundary?
What proportion of the points in a hypercube of dimension 50 are in the boundary?A hypercube with side length 1 in d dimensions is defined to be the set of points $(x_1, x_2, ..., x_d)$ such that $0≤xj≤1$ for all $j = 1, 2, ..., d$ ...
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What are the requirements for a well-defined machine learning task?
What are the requirements for a well-defined machine learning task?What are the requirements for a well-defined machine learning task? ...
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What are approaches of supervised models where the dimension of independent variables is not fixed?
What are approaches of supervised models where the dimension of independent variables is not fixed?In supervised models a dependent variable y is predicted from a number of features x_1, x_2, ... ,x_n . Usually &nbsp;n is fixed and small. An example ...
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What is a sample space in probability theory?
What is a sample space in probability theory?What is a sample space in probability theory? ...
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How is dimensionality related to overfitting and underfitting?
How is dimensionality related to overfitting and underfitting?How is dimensionality related to overfitting and underfitting? ...
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How does a machine learning researcher know the difference between local and global minima?
How does a machine learning researcher know the difference between local and global minima?How does a machine learning researcher know the difference between local and global minima? ...
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How does an algorithm traverse the solution space in order to determine the optimal solution?
How does an algorithm traverse the solution space in order to determine the optimal solution?How does an algorithm traverse the solution space in order to determine the optimal solution? ...
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What is the best way to split training and testing data in machine learning?