• Complain
LitArk » Books » Computer

Tshepo Chris Nokeri - Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps

Here you can read online Tshepo Chris Nokeri - Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2021, publisher: Apress, genre: Computer. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:

Romance novel Science fiction Adventure Detective Science History Home and family Prose Art Politics Computer Non-fiction Religion Business Children Humor

Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.

Tshepo Chris Nokeri Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps
  • Book:
    Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps
  • Author:
  • Publisher:
    Apress
  • Genre:
  • Year:
    2021
  • Rating:
    5 / 5
  • Favourites:
    Add to favourites
  • Your mark:
    • 100
    • 1
    • 2
    • 3
    • 4
    • 5

Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps: summary, description and annotation

We offer to read an annotation, description, summary or preface (depends on what the author of the book "Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.

Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps.

Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, hell show you the key Python web frameworks and techniques for building web apps with them. Youll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. Youll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms.

Web App Development and Real-Time Web Analytics with Python is ideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning.

What You Will Learn

  • Create interactive graphs and render static graphs into interactive ones
  • Understand the essentials of HTML, CSS, and Bootstrap
  • Gain insight into the key Python web frameworks, and how to develop web applications using them
    • Develop machine learning algorithms and integrate them into web apps
  • Secure web apps and deploy them to cloud platforms

Who This Book Is For

Intermediate data scientists, machine learning engineers, and web developers.

Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps — read online for free the complete book (whole text) full work

Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.

Light

Font size:

↓
↑
Reset

Interval:

↓
↑

Bookmark:

Make
1234567...56
Contents
Landmarks
Book cover of Web App Development and Real-Time Web Analytics with Python - photo 1
Book cover of Web App Development and Real-Time Web Analytics with Python
Tshepo Chris Nokeri
Web App Development and Real-Time Web Analytics with Python
Develop and Integrate Machine Learning Algorithms into Web Apps
1st ed.
Logo of the publisher Tshepo Chris Nokeri Pretoria South Africa ISBN - photo 2
Logo of the publisher
Tshepo Chris Nokeri
Pretoria, South Africa
ISBN 978-1-4842-7782-9 e-ISBN 978-1-4842-7783-6
https://doi.org/10.1007/978-1-4842-7783-6
Tshepo Chris Nokeri 2022
Apress Standard
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Apress imprint is published by the registered company APress Media, LLC part of Springer Nature.

The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

I would like dedicate this book to my family, friends, and anyone who played a pivotal role in any aspect of my life, including the Apress team for the continous support.

Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the books product page, located at www.apress.com/9781484277829. For more detailed information, please visit http://www.apress.com/source-code.

Acknowledgments

Writing a single-authored book is demanding, but I received firm support and active encouragement from my family and dear friends. Many heartfelt thanks to the Apress team for their backing throughout the writing and editing process. And my humble thanks to all of you for reading this; I earnestly hope you find it helpful.

Table of Contents
About the Author
Tshepo Chris Nokeri
harnesses advanced analytics and artificial intelligence to foster innovation - photo 3
harnesses advanced analytics and artificial intelligence to foster innovation and optimize business performance. He delivers complex solutions to companies in the mining, petroleum, and manufacturing industries. He received a bachelors degree in information management. He graduated with honours in business science from the University of the Witwatersrand, Johannesburg, on a Tata Prestigious Scholarship and a Wits Postgraduate Merit Award. He was unanimously awarded the Oxford University Press Prize. Tshepo has authored three books: Data Science Revealed (Apress, 2021), Implementing Machine Learning in Finance (Apress, 2021), and Econometrics and Data Science (Apress, 2022).
About the Technical Reviewer
Brij Kishore Pandey
works as a software engineer architect and strategist at ADP He has a wide - photo 4
works as a software engineer, architect, and strategist at ADP. He has a wide interest in software development using cutting-edge tools/technologies in cloud computing, data engineering, data science, artificial intelligence, and machine learning. He has 12 years of experience working with global corporate leaders, including JP Morgan Chase, American Express, 3M Company, Alaska Airlines, Cigna Healthcare, and ADP.
The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
T. C. Nokeri Web App Development and Real-Time Web Analytics with Python https://doi.org/10.1007/978-1-4842-7783-6_1
1. Tabulating Data and Constructing Static 2D and 3D Charts
Tshepo Chris Nokeri
(1)
Pretoria, South Africa

This chapter introduces the basics of tabulating data and constructing static graphical representations. It begins by demonstrating an approach to extract and tabulate data by implementing the pandas and SQLAlchemy libraries. Subsequently, it reveals two prevalent 2D and 3D charting libraries: Matplotlib and seaborn. It then describes a technique for constructing basic charts (i.e., box-whisker plot, histogram, line plot, scatter plot, density plot, violin plot, regression plot, joint plot, and heatmap).

Tabulating the Data

The most prevalent Python library for tabulating data comprising rows and columns is pandas. Ensure that you install pandas in your environment. To install pandas in a Python environment, use pip install pandas . Likewise, in a conda environment, use conda install -c anaconda pandas .

The book uses Python version 3.7.6 and pandas version 1.2.4. Note that examples in this book also apply to the latest versions.

Listing extracts data from a CSV file by implementing the pandas library.
import pandas as pd
df = pd.read_csv(r"filepath\.csv")
Listing 1-1

Extracting a CSV File Using Pandas

Listing extracts data from an Excel file by implementing pandas.
df = pd.read_excel(r"filepath\.xlsx")
Listing 1-2

Extracting an Excel File Using Pandas

Notice the difference between Listings ).

In a case where there is sequential data and you want to set the datetime as an index, specify the column for parsing, including parse_dates and indexing data using index_col , and then specify the column number (see Listing ).
df = pd.read_csv(r"filepath\.csv", parse_dates=[0], index_col=[0])
Listing 1-3

Sparse and Index pandas DataFrame

Alternatively, you may extract the data from a SQL database.

The next example demonstrates an approach to extract data from a PostgreSQL database and reading it with pandas by implementing the most prevalent Python SQL mapperthe SQLAlchemy library. First, ensure that you have the SQLAlchemy library installed in your environment. To install it in a Python environment, use pip install SQLAlchemy . Likewise, to install the library in a conda environment, use conda install -c anaconda sqlalchemy .

Listing extracts a table from PostgreSQL, assuming the username is "test_user" and the password is "password123" , the port number is "8023" , the hostname is "localhost" , the database name is "dataset" , and the table is "dataset" . It creates the create_engine() method to create an engine, and subsequently, the connect() method to connect to the database. Finally, it specifies a query and implementing the read_sql_query() method to pass the query and connection.
import pandas as pd
import sqlalchemy
from sqlalchemy import create_engine
from sqlalchemy import Table, Column, String, MetaData
Next page
1234567...56
Light

Font size:

↓
↑
Reset

Interval:

↓
↑

Bookmark:

Make

Similar books «Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps»

Look at similar books to Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.


Oliver R. Simpson - PYTHON: 4 BOOKS IN 1: Learn How To Develop Programs And Apps In 7 Days With Python Programming And Start Deep Hands-on Learning For Beginners of Data Science And Machine Learning.
PYTHON: 4 BOOKS IN 1: Learn How To Develop Programs And Apps In 7 Days With Python Programming And Start Deep Hands-on Learning For Beginners of Data Science And Machine Learning.
Oliver R. Simpson
PYTHON: 4 BOOKS IN 1: Learn How To Develop Programs And Apps In 7 Days With Python Programming And Start Deep Hands-on Learning For Beginners of Data Science And Machine Learning.
Tshepo Chris Nokeri - Implementing Machine Learning for Finance
Implementing Machine Learning for Finance
Tshepo Chris Nokeri
Implementing Machine Learning for Finance
Tshepo Chris Nokeri - Data Science Solutions with Python: Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn
Data Science Solutions with Python: Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn
Tshepo Chris Nokeri
Data Science Solutions with Python: Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn
Elias Dabbas - Interactive Dashboards and Data Apps with Plotly and Dash
Interactive Dashboards and Data Apps with Plotly and Dash
Elias Dabbas
Interactive Dashboards and Data Apps with Plotly and Dash
Shovic John C. - Python All-in-One For Dummies
Python All-in-One For Dummies
Shovic John C.
Python All-in-One For Dummies
Ramalingam Ganapathy - Learning Google Apps Script: customize and automate Google Applications using Apps Script
Learning Google Apps Script: customize and automate Google Applications using Apps Script
Ramalingam Ganapathy
Learning Google Apps Script: customize and automate Google Applications using Apps Script
Jonathan Stark - Building iPhone Apps with HTML, CSS, and JavaScript
Building iPhone Apps with HTML, CSS, and JavaScript
Jonathan Stark
Building iPhone Apps with HTML, CSS, and JavaScript
Coleman Jason - Building Web Apps with WordPress [WordPress as an application framework]
Building Web Apps with WordPress [WordPress as an application framework]
Coleman Jason
Building Web Apps with WordPress [WordPress as an application framework]
No cover
No cover
Anubhav Singh
Hands-On Python Deep Learning for the Web: Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow
Alberto Artasanchez - Artificial Intelligence with Python: Your complete guide to building intelligent apps using Python 3.x and TensorFlow 2
Artificial Intelligence with Python: Your complete guide to building intelligent apps using Python 3.x and TensorFlow 2
Alberto Artasanchez
Artificial Intelligence with Python: Your complete guide to building intelligent apps using Python 3.x and TensorFlow 2
Jonathan Stark - Building Android Apps with HTML, CSS, and JavaScript: Making Native Apps with Standards-Based Web Tools
Building Android Apps with HTML, CSS, and JavaScript: Making Native Apps with Standards-Based Web Tools
Jonathan Stark
Building Android Apps with HTML, CSS, and JavaScript: Making Native Apps with Standards-Based Web Tools
Rob Warner - Beginning Mac OS X Lion Apps Development
Beginning Mac OS X Lion Apps Development
Rob Warner
Beginning Mac OS X Lion Apps Development
Reviews about «Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps»

Discussion, reviews of the book Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms into Web Apps and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.