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A high-degree polynomial model is likely to have:
high variance and thus overfit
high variance and thus underfit
low variance and thus overfit
low variance and thus underfit
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1 Machine Learning Training Models Part-1
2 Machine Learning Training Models Part-2
3 Machine Learning Training Models Part-3
4 Machine Learning Training Models Part-4
5 Machine Learning Training Models Part-5
6 Training Models - MCQs - Which of these will have a better chance of giving...
7 Training Models - MCQs - Which of these can be used to reduce the Irreducible...
8 Training Models - MCQs - Which of these is faster for large number of datasets?...
9 Training Models - MCQs - Which of these will you use when there are small...
10 Training Models - MCQs - Which of these will you use when there are large...
11 Training Models - MCQs - Batch Gradient Descent involves calculations over the full training set...
12 Training Models - MCQs - For linear regression problems, MSE is a convex function and...
13 Training Models - MCQs - Training Linear Regression model using Normal Equation is linear with...
14 Training Models - MCQs - Prediction using Linear Regression model is linear with both the...
15 Training Models - MCQs - Which of these is more prone to overfitting?...
16 Training Models - MCQs - RMSE is more sensitive to outliers than MAE. True or...
17 Training Models - MCQs - The higher the norm index would imply:...
18 Training Models - MCQs - Logitic regression is a...
19 Training Models - MCQs - What will be the output of the following code snippet?
20 Training Models - MCQs - Which of the following libraries can be used for linear...
21 Training Models - MCQs - Vector addition is commutative and associative?...
22 Training Models - MCQs - What is the dot product impelementation in numpy?
23 Training Models - MCQs - u = [1,2,3] and v = [3,4,5]. u * v...
24 Training Models - MCQs - Dot product is commutative...
25 Training Models - MCQs - Dot product between a vector and a scalar is not...
26 Training Models - MCQs - Is dot product of three vectors associative?...
27 Training Models - MCQs - If u.v = 0 where u and v are vectors,...
28 Training Models - MCQs - If u.v = 0 where u and v are vectors,...
29 Training Models - MCQs - Ridge regression uses which norm?...
30 Training Models - MCQs - Lasso regression uses which norm?...
31 Training Models - MCQs - Elastic Net uses which norm?...
32 Training Models - MCQs - For SGD, the solution is good but not optimal, true...
33 Training Models - MCQs - Which of these should be used for small training datasets?...
34 Training Models - MCQs - Which of these is an iterative way of training a...
35 Training Models - MCQs - In the normal equation, what is the size of of...
36 Training Models - MCQs - In the normal equation, we need to calculate the inverse...
37 Training Models - MCQs - In the normal equation, the computational complexity of calculating the...
38 Training Models - MCQs - In the normal equation, the computational complexity of calculating the...
39 Training Models - MCQs - Should we use normal equation for solving linear models with...
40 Training Models - MCQs - Should we use Batch Gradient Descent for solving linear models...
41 Training Models - MCQs - Batch Gradient Descent scales well with number of training datasets?...
42 Training Models - MCQs - Batch Gradient Descent scales well with number of features?...
43 Training Models - MCQs - How to determine a good learning rate for batch gradient...
44 Training Models - MCQs - In Batch Gradient Descent, convergence rate decreases with increase in...
45 Training Models - MCQs - A high-degree polynomial model is likely to have:...
46 Training Models - MCQs - In SGD, the solution never settles down. To solve this...
47 Training Models - MCQs - Which of the following Scikit class can be used for...
48 Training Models - MCQs - In mini-batch gradient descent, the path taken is less erratic...
49 Training Models - MCQs - It is harder for mini-batch gradient descent than SGD to...
50 Training Models - MCQs - NormalEquation class in scikit learn solve linear regression using:...
51 Training Models - MCQs - Which of these provide out-of-core support for linear regression?...
52 Training Models - MCQs - What will be the number of features after using Polynomial...
53 Training Models - MCQs - A high-degree polynomial feature can lead to:...
54 Training Models - MCQs - In over-fitting, the performance of the model generalizes well. True...
55 Training Models - MCQs - One way to improve an overfitting model is:...
56 Training Models - MCQs - A model's generalization error can expressed as a sum of...
57 Training Models - MCQs - A high-bias model is most like to:...
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