Python - Advanced Operations with NumPy Arrays
Python
| Intermediate
- 13 videos | 1h 7m 19s
- Includes Assessment
- Earns a Badge
NumPy is oneof the fundamental packages for scientific computing that allows data to be represented in dimensional arrays. This course covers the array operations you can undertake such as image manipulation, fancy indexing, and broadcasting. To take this Skillsoft Aspire course, you should be comfortable with how to create, index, and slice Numpy arrays, and apply aggregate and universal functions. Among the topics, you will learn about the several options available in NumPy to split arrays. You will learn how to use NumPy to work with digital images, which are multidimensional arrays. Next, you will observe how to manipulate a color image, perform slicing operations to view sections of the image, and use a SciPy package for image manipulation. You will learn how to use masks, an array of index values, to access multiple elements of an array simultaneously, referred to as Sansi indexing. Finally, this course covers broadcasting to perform operations between mismatched arrays.
WHAT YOU WILL LEARN
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Identify different ways in which arrays can be split up
Describe how grayscale and color images can be represented as multi-dimensional arrays
Perform some basic image manipulation after converting images to arrays
Create a view into a numpy array and learn of the relationship between views and their base arrays
Compare deep copies of arrays with views and know when to use each of them
Use fancy indexing with arrays using an index mask -
Use fancy indexing to analyze real-world data
Apply boolean masks to access array elements which fulfil a specific condition
Use structured arrays in order to store heterogeneous data
Describe how operations can be performed between arrays of mismatched shapes using broadcasting
Perform operations between arrays of mismatched shapes by applying broadcasting rules
Utilize numpy to perform multi-dimensional array operations
IN THIS COURSE
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1m 58s
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4m 38sDuring this video, you will learn how to identify different ways arrays can be split up. FREE ACCESS
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3. Images as Arrays4m 35sUpon completion of this video, you will be able to describe how grayscale and color images can be represented as multidimensional arrays. FREE ACCESS
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4. Image Manipulation Using NumPy6m 59sIn this video, you will perform some basic image manipulation after converting images to arrays. FREE ACCESS
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5. Views and NumPy Arrays4m 36sFind out how to create a view into a NumPy array and learn about the relationship between views and their base arrays. FREE ACCESS
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6. Deep Copies of Arrays2m 25sFind out how to compare deep copies of arrays with views, and know when to use each of them. FREE ACCESS
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7. Introduction to Index Masks5m 29sLearn how to use fancy indexing with arrays using an index mask. FREE ACCESS
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8. Applying Index Masks8m 44sIn this video, learn how to use indexing to analyze real-world data. FREE ACCESS
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9. Indexing with Boolean Masks5m 28sIn this video, find out how to apply boolean masks to access array elements which fulfill a specific condition. FREE ACCESS
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10. Structured Arrays4m 40sIn this video, you will use structured arrays to store heterogeneous data. FREE ACCESS
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11. Understanding Array Broadcasting7m 39sAfter completing this video, you will be able to describe how operations can be performed between arrays of mismatched shapes using broadcasting. FREE ACCESS
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12. Applying Broadcasting Rules on Array Operations5m 39sIn this video, find out how to perform operations between arrays of mismatched shapes by applying broadcasting rules. FREE ACCESS
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13. Exercise: NumPy Multi-dimensional Array Operations4m 31sIn this video, learn how to use NumPy to perform multi-dimensional array operations. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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