The Data Science Workshop Learn how you can build machine learning models and create your own real-world data science projects

Synopsis

Gain expert guidance on how to successfully develop machine learning models in Python and build your own unique data platforms
Key Features
Gain a full understanding of the model production and deployment process
Build your first machine learning model in just five minutes and get a hands-on machine learning experience
Understand how to deal with common challenges in data science projects
Book Description
Where there's data, there's insight. With so much data being generated, there is immense scope to extract meaningful information that'll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you'll open new career paths and opportunities.
The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You'll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you'll get hands-on with approaches such as grid search and random search.
Next, you'll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You'll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch.
By the end of this book, you'll have the skills to start working on data science projects confidently. By the end of this book, you'll have the skills to start working on data science projects confidently.
What you will learn
Explore the key differences between supervised learning and unsupervised learning
Manipulate and analyze data using scikit-learn and pandas libraries
Understand key concepts such as regression, classification, and clustering
Discover advanced techniques to improve the accuracy of your model
Understand how to speed up the process of adding new features
Simplify your machine learning workflow for production
Who this book is for
This is one of the most useful data science books for aspiring data analysts, data scientists, database engineers, and business analysts. It is aimed at those who want to kick-start their careers in data science by quickly learning data science techniques without going through all the mathematics behind machine learning algorithms. Basic knowledge of the Python programming language will help you easily grasp the concepts explained in this book.

Book details

Author:

Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, Dr. Samuel Asare

ISBN:

9781800569409

Publisher:

Packt Publishing

Pages:

N/A

Reading age:

Not specified

Includes images:

Yes

Date of addition:

2020-09-03

Usage restrictions:

Copyright

Copyright date:

2020

Copyright by:

Packt Publishing Pvt. Ltd. 

Adult content:

No

Language:

English

Categories:

Computers and Internet, Nonfiction