پایتون ( Machine Learning | Data Science )

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#NumPy cheat sheet for #datascience :

*Array Creation*

1. numpy.array() - Create an array from a list or other iterable.
2. numpy.zeros() - Create an array filled with zeros.
3. numpy.ones() - Create an array filled with ones.
4. numpy.empty() - Create an empty array.
5. numpy.arange() - Create an array with evenly spaced values.
6. numpy.linspace() - Create an array with evenly spaced values.

*Array Operations*

1. + - Element-wise addition.
2. - - Element-wise subtraction.
3. * - Element-wise multiplication.
4. / - Element-wise division.
5. ** - Element-wise exponentiation.
6. numpy.sum() - Sum of all elements.
7. numpy.mean() - Mean of all elements.
8. numpy.median() - Median of all elements.
9. numpy.std() - Standard deviation.
10. numpy.var() - Variance.

*Array Indexing*

1. arr[i] - Access ith element.
2. arr[i:j] - Access slice from ith to jth element.
3. arr[i:j:k] - Access slice with step k.

*Array Reshaping*

1. arr.reshape() - Reshape array.
2. arr.flatten() - Flatten array.
3. arr.ravel() - Flatten array.

*Array Manipulation*

1. numpy.concatenate() - Concatenate arrays.
2. numpy.split() - Split array.
3. numpy.transpose() - Transpose array.
4. numpy.flip() - Flip array.

*Mathematical Functions*

1. numpy.sin() - Sine.
2. numpy.cos() - Cosine.
3. numpy.tan() - Tangent.
4. numpy.exp() - Exponential.
5. numpy.log() - Natural logarithm.

*Statistical Functions*

1. numpy.min() - Minimum value.
2. numpy.max() - Maximum value.
3. numpy.percentile() - Percentile.
4. numpy.quantile() - Quantile.

*Random Number Generation*

1. numpy.random.rand() - Random numbers.
2. numpy.random.normal() - Normal distribution.
3. numpy.random.uniform() - Uniform distribution.

*Linear Algebra*

1. numpy.dot() - Dot product.
2. numpy.matmul() - Matrix multiplication.
3. numpy.linalg.inv() - Matrix inverse.

#cheat_sheet #Python
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پایتون ( Machine Learning | Data Science )