python for data science - Softcover

Charles, Tony F.

Softcover

ISBN 10: 1801115990 ISBN 13: 9781801115995

Verlag: tony f. charles, 2020

Inhaltsangabe

Are you looking for a beginners guide?

Do you want to learn how to use python for beginners in a simple way?

Do you want to enter into the new world of Python for beginners in an efficient and effective way?

 This book will teach you the basics as well as the advanced concepts of computers and programming. The gaming industry is growing rapidly and Python offers a lot of libraries to create games. Many tech giants rely on Python to deliver world-class applications.

In This book you will learn:

• Python setup
• Anaconda
• Winpython
• Data science packeges
• Jupyter
• Data munging with pandas
• The process
• Importing datasets
• Data preprocessing
• The data science pipeline
• Principal component analysis
• Supervised learning algorithms
• Analyzing big data
• Neural networks structures
• Classification and regression trees
• The overfitting problem
• New features
• Naïve bayes classifier
• Linear regression
• Logistic regression
• Support vector machine
• Applications in the real world
• Pruning
• Data selection

   This book is not just a startup guide. This book will prove beneficial for years to come. The book has the latest codes and techniques so you can equip your skills according to the current market challenges. After all, the purpose is to land a nicely paid job in a globally recognized firm. This book will help you reach that goal!

Most people can learn how to code but not just anyone can code smartly. This book is going to help you to think out of the box and take on problems with a completely different perspective. The tricks mentioned will make you invaluable to any software development firm.

Details zur Ausgabe

• Verlag: tony f. charles
• Erscheinungsdatum: 2020
• Sprache: Englisch
• ISBN 10: 1801115990
• ISBN 13: 9781801115995
• Einband: Tapa blanda
• Anzahl der Seiten: 138
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Nicht verfügbar