Introduction to Symbolic Algebra using SymPy SciPy in this video tutorial by Charles Kelly. These are explained in the context of computer science and data science to technologists and students in preparation for machine learning, applied statistics, neur
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- Exercise Files
- [Narrator] The Finding Pattern file…in you exercises files folder…is pre-populated with an import statement…and a list of numbers that is stored in an array…called my teaser array.…The goal of this video is to find the pattern…within these numbers.…In this video, we'll use NumPy plus SymPy…to find the pattern within the dataset.…SymPy is a Python library…that provides symbolic calculations.…Finding a pattern within a dataset is a common problem.…
The fields of applied statistics,…artificial intelligence,…neural networks and machine learning,…have multiple techniques for finding patterns…within datasets.…Before we discover the pattern for this dataset,…pause the video,…examine the dataset and attempt to find the pattern.…Before using this notebook,…go to the cell menu…and select run all.…Sometimes when a pattern is not relatively apparent…within a dataset,…the differences between the elements of a dataset…may provide a pattern.…
Difference equations are mathematical constructs…that provide methods for analyzing differences…
- Using Jupyter Notebook
- Creating NumPy arrays from Python structures
- Slicing arrays
- Using Boolean masking and broadcasting techniques
- Plotting in Jupyter notebooks
- Joining and splitting arrays
- Rearranging array elements
- Creating universal functions
- Finding patterns
- Building magic squares and magic cubes with NumPy and Python
Skill Level Intermediate
2. Create NumPy Arrays
3. Index, Slice, and Iterate
4. Plots: Matplotlib and Pyplot
5. Manipulate Arrays
6. Short Examples
7. Extended Examples
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