Machine Learning-Based Mobile Applications Using Python and Scikit-Learn

Machine Learning-Based Mobile Applications Using Python and Scikit-Learn

Copyright: © 2023 |Pages: 25
DOI: 10.4018/978-1-6684-8582-8.ch016
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Abstract

This chapter gives a broad outline of machine learning on Android mobile phones using the Scikit-learn module. The first section introduces the reader to Python language; next, Python on Android is introduced with a brief historical note on implementations of Python on Android mobile phones. Pydroid3 is introduced in the subsequent section. This is followed by instructions on setting up an Android phone for machine learning. This is followed by a description of supportive modules for machine learning that are available for Pydroid3, and some example codes, namely: os, pathlib, Pandas, NumPy, SciPy, Matplotlib, Seaborn, PySimpleGUI, NetworkX, Biopython, WordCloud, Kivy, and Jupyter Notebook. The last section of this compilation describes the Scikit-learn library, basic concepts of the Scikit-learn module, and algorithms available with this module, namely: Linear Regression, Logistic Regression, Principal Component Analysis (PCA), XGBoost, K-nearest neighbors, and support vector machine.
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The Power Of Python From The Smallest To The Largest

In contrast despite its obvious simplicity Python is a powerful language capable of implementing many complex ML algorithms using vast collection of additional libraries. On the other hand Python can also be used to automate common menial tasks like for instance, document conversions (docx2pdf, pdfplumber,PyPDF2), creating PowerPoints (pptx), taking screenshot, copy and paste text from the system clipboard (pyperclip), merging word documents (docx), manipulate Excel sheets (openpyxl), image background removal (rembg)or lookup a stock price(yfinance) or lookup currency exchange rate (forex_python) or changing colour images to greyscale (pillow) or spell-check a text (textblob) or download a file (urlib). Office automation task to complex Machine learning algorithms like for instance, Distributed Evolutionary Algorithms in Python (DEAP) (deap module) and Symbolic mathematics (sympy).DEAP gives the power of mathematical modelling, optimization, genetic programing, particle swarm optimization, and evolution strategies. Many of these modules are also available via pip on Pydroid3 and code conveniently tested on Android itself. Even the complex module deap is obtainable on Android. Python is indeed the Swiss army knife of programming language.

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