Titlebook: Artificial Intelligence with Python; Teik Toe Teoh,Zheng Rong Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exclusi

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https://doi.org/10.1007/978-1-84882-653-3nd can be used as a form of feature engineering. The Apriori algorithm covered, mines for frequent itemsets and association rules in a database. Support, Lift, Conviction, and Confidence are important values that represent the strength of an association.

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Application to a Winding Machine,-image, and Pillow are useful tools that make image processing simpler. Techniques covered include generating histograms, extracting contours, grayscale transformation, histogram equalization, Fourier transformation, high pass filtering, and pattern recognition. A template matching example shown wil

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Python for Artificial Intelligence all around the world use Python. This chapter will provide an introduction to the Python Programming Language before covering its history and common uses and explain why it is so popular among Artificial Intelligence developers.

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Getting Startedrocess. Jupyter Notebook and Anaconda are very useful tools that will make programming in Python simpler for learners and are commonly used in the industry. Setting up your development environment will be simple to achieve through following our step-by-step guide.

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Data Wranglinglls are needed to create efficient ETL pipelines for usable data. There are many functions in Pandas that allow us to deal with a wide variety of circumstances. This chapter will illustrate how to handle Missing Data Values, Duplicates, Mapping Values, Outliers, Permutations, Merging and Combining, Reshaping, and Pivoting.