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You're reading from  Applied Supervised Learning with Python

Product typeBook
Published inApr 2019
Reading LevelIntermediate
Publisher
ISBN-139781789954920
Edition1st Edition
Languages
Python
Tools
TensorFlow
Concepts
Neural Networks
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Authors (2):
Benjamin Johnston
Benjamin Johnston
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Benjamin Johnston

Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.
Read more about Benjamin Johnston

Ishita Mathur
Ishita Mathur
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Ishita Mathur

Ishita Mathur has worked as a data scientist for 2.5 years with product-based start-ups working with business concerns in various domains and formulating them as technical problems that can be solved using data and machine learning. Her current work at GO-JEK involves the end-to-end development of machine learning projects, by working as part of a product team on defining, prototyping, and implementing data science models within the product. She completed her masters' degree in high-performance computing with data science at the University of Edinburgh, UK, and her bachelor's degree with honors in physics at St. Stephen's College, Delhi.
Read more about Ishita Mathur

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Introduction

Say we have a problem statement that involves predicting whether a particular earthquake caused a tsunami or not. How do we decide what model to use? What do we know about the data we have? Nothing! But if we don't know and understand our data, chances are we'll end up building a model that's not very interpretable or reliable.

When it comes to data science, it's important to have a thorough understanding of the data we're dealing with, in order to generate features that are highly informative and, consequently, to build accurate and powerful models.

In order to gain this understanding, we perform an exploratory analysis on the data to see what the data can tell us about the relationships between the features and the target variable. Getting to know our data will even help us interpret the model we build and identify ways we can improve its accuracy.

The approach we take to achieve this is to allow the data to reveal its structure or model, which helps gain some new, often unsuspected...

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Applied Supervised Learning with Python
Published in: Apr 2019Publisher: ISBN-13: 9781789954920
© 2019 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
Benjamin Johnston

Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.
Read more about Benjamin Johnston

author image
Ishita Mathur

Ishita Mathur has worked as a data scientist for 2.5 years with product-based start-ups working with business concerns in various domains and formulating them as technical problems that can be solved using data and machine learning. Her current work at GO-JEK involves the end-to-end development of machine learning projects, by working as part of a product team on defining, prototyping, and implementing data science models within the product. She completed her masters' degree in high-performance computing with data science at the University of Edinburgh, UK, and her bachelor's degree with honors in physics at St. Stephen's College, Delhi.
Read more about Ishita Mathur

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