Data Science - Machine Learning Basics Flashcards

1
Q

Bias variance trade off

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Common pitfalls of PCA

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Bias variance tradeoff math

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Favorite machine learning algorithm

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

EIgen vector

A

For some nxn matrix A, x is an eigenvector of A if Ax = lamdba x where lambda is a scalr.

A matrix can represrnt linear transformation and when it is applied to a vector x, results in an eigen vector

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

eigenvalue

A

Scaling value lambda

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

eigendecomposition

A

decomposition of a squared matrix into its eigenvectors

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

SVD

A

non-square matrices are decomposed using SVD

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Loss function

A

Tells us how well a model fits a particular dataset. The lower the loss, the more desirable.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Optimization methods

A

Technoques for minimizing a cost function

How well did you know this?
1
Not at all
2
3
4
5
Perfectly