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Python: Data Analytics and Visualization

You're reading from Python: Data Analytics and Visualization Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python

Product type Course

Published in Mar 2017

Publisher Packt

ISBN-13 9781788290098

Length 866 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Authors (4):

Martin Czygan

Phuong Vo.T.H

Ashish Kumar

Kirthi Raman

View More author details

Table of Contents (6) Chapters

Preface

1. Module 1 FREE CHAPTER

2. Module 2

3. Module 3

Bibliography

Index

Chapter 9. Best Practices for Predictive Modelling

As we have seen in all the chapters on the modelling techniques, a predictive model is nothing but a set of mathematical equations derived using a few lines of codes. In essence, this code together with a slide-deck highlighting the high-level results from the model constitute a project. However, the user of our solution is more interested in finding a solution for the problem he is facing in the business context. It is the responsibility of the analyst or the data scientist to offer the solution in a way that is user-friendly and maximizes output or insights.

There are some general guidelines that can be followed for the optimum results in a predictive modelling project. As predictive modelling comprises a mix of computer science techniques, algorithms, statistics, and business context capabilities, the best practices in the predictive modelling are a total of the best practices in the aforementioned individual fields.

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Authors (4)

Martin Czygan

Martin Czygan

Martin Czygan studied German literature and computer science in Leipzig, Germany. He has been working as a software engineer for more than 10 years. For the past eight years, he has been diving into Python, and is still enjoying it. In recent years, he has been helping clients to build data processing pipelines and search and analytics systems.

See other products by Martin Czygan

Phuong Vo.T.H

Phuong Vo.T.H

Phuong Vo.T.H has a MSc degree in computer science, which is related to machine learning. After graduation, she continued to work in some companies as a data scientist. She has experience in analyzing users' behavior and building recommendation systems based on users' web histories. She loves to read machine learning and mathematics algorithm books, as well as data analysis articles.

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Ashish Kumar

Ashish Kumar

Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.

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Kirthi Raman

Kirthi Raman

Kirthi Raman is currently working as a lead data engineer with Neustar Inc, based

See other products by Kirthi Raman

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