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`@@ -19,44 +19,3 @@ This book covers the following exciting features:`
`19`	`19`	`* Understand how to transform, discretize, and scale your variables`
`20`	`20`	`* Create informative variables from date and time`
`21`	`21`
`22`		`-If you feel this book is for you, get your [copy](https://www.amazon.com/dp/1789806313) today!`
`23`		`-`
`24`		`-<a href="https://www.packtpub.com/?utm_source=github&utm_medium=banner&utm_campaign=GitHubBanner"><img src="https://raw.githubusercontent.com/PacktPublishing/GitHub/master/GitHub.png" alt="https://www.packtpub.com/" border="5" /></a>`
`25`		`-`
`26`		`-## Instructions and Navigations`
`27`		`-All of the code is organized into folders.`
`28`		`-`
`29`		`-The code will look like the following:`
`30`		-```
`31`		`-def get_first_cabin(row):`
`32`		`- try:`
`33`		`- return row.split()[0]`
`34`		`- except:`
`35`		`- return np.nan`
`36`		-```
`37`		`-`
`38`		`-Following is what you need for this book:`
`39`		`-This book is for machine learning professionals, AI engineers, data scientists, and NLP and reinforcement learning engineers who want to optimize and enrich their machine learning models with the best features. Knowledge of machine learning and Python coding will assist you with understanding the concepts covered in this book.`
`40`		`-`
`41`		`-With the following software and hardware list you can run all code files present in the book (Chapter 1-11).`
`42`		`-`
`43`		`-### Software and Hardware List`
`44`		`-`
`45`		`-\| Chapter \| Software required \| OS required \|`
`46`		`-\| -------- \| -------------------------------------------------------------------------------------\| -----------------------------------\|`
`47`		`-\| 1 - 11 \| Python 3.5+, Anaconda Distibution, IDE(personal preference) \| Windows, Mac OS X, and Linux (Any) \|`
`48`		`-`
`49`		`-We also provide a PDF file that has color images of the screenshots/diagrams used in this book. [Click here to download it](https://static.packt-cdn.com/downloads/9781789806311_ColorImages.pdf).`
`50`		`-`
`51`		`-`
`52`		`-### Related products <Other books you may enjoy>`
`53`		`-* Python Machine Learning Cookbook - Second Edition [[Packt]](https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning-cookbook-second-edition-0?utm_source=github&utm_medium=repository&utm_campaign=9781789808452) [[Amazon]](https://www.amazon.com/Python-Machine-Learning-Cookbook-real-world/dp/1789808456)`
`54`		`-`
`55`		`-* Python Machine Learning By Example - Second Edition [[Packt]](https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning-example-second-edition?utm_source=github&utm_medium=repository&utm_campaign=9781789616729) [[Amazon]](https://www.amazon.com/Python-Machine-Learning-Example-intelligent/dp/1789616727)`
`56`		`-`
`57`		`-## Get to Know the Author`
`58`		`-Soledad Galli`
`59`		-is a lead data scientist with more than 10 years of experience in world-class academic institutions and renowned businesses. She has researched, developed, and put into production machine learning models for insurance claims, credit risk assessment, and fraud prevention. Soledad received a Data Science Leaders' award in 2018 and was named one of LinkedIn's voices in data science and analytics in 2019. She is passionate about enabling people to step into and excel in data science, which is why she mentors data scientists and speaks at data science meetings regularly. She also teaches online courses on machine learning in a prestigious Massive Open Online Course platform, which have reached more than 10,000 students worldwide.
`60`		`-`
`61`		`-### Suggestions and Feedback`
`62`		`-[Click here](https://docs.google.com/forms/d/e/1FAIpQLSdy7dATC6QmEL81FIUuymZ0Wy9vH1jHkvpY57OiMeKGqib_Ow/viewform) if you have any feedback or suggestions.`

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