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Learning Data Science with Python can be intimidating at times due to the requirements of programming and mathematical knowledge. Because of this "fear," this guidebook aims to demystify complex technical concepts. One of the main goals of this book is to explain everything at a basic level so that everyone can understand what Data Science is all about.
This book carefully guides you through how to install Python together with all the packages and tools you need to assist you along the way.
You will also go through a chapter about programming concepts, where you will learn about basic data types in programming and Python's syntax. There will be examples of code guiding you through each concept, with clear explanations.
You will also learn about tools specifically used by data scientists. You will be guided on how to install them, how to prepare them for work, and how to implement them in your own projects.
We have to work through the collection of raw data, cleaning off and organizing the data that we have, learning what insights are there, figuring out the best model to work with and training and testing it, and then completing the analysis as well. We will take some time to discuss all of these parts and more as we worked through this guidebook and figure out the best way to make these works for us as well.
Working with Data Science is something that all businesses are able to use to help them get ahead and really see some results in the process. But it is a process that takes time and is not always as easy to complete as we might hope. With the help of this guidebook, and some of the tools that we have discussed inside, get ready to use Python Data Science for your needs.
"Python for Data Science" has emphasized that the long-term contributions of Data Science to multiple fields are founded on its grasps Deep Learning, Machine Learning, and the use of prominent applications such as Python.
With this book in your hands, you will:
- Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops
- Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism
- Discover the importance of Data Science and how to use it in real-world situations
- Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn
- Discover how companies can improve their business through practical examples and explanations
- And Much More!
Learning Data Science is not an independent process where you can learn each concept separately from one another. It is a continuous process of applying previous knowledge into a new application. Therefore, having an understanding of the concepts would ensure that you are equipped to learn more but also ready to put this knowledge into use. Learning Data Science encourages us to both use it at its best but also be aware of its limitations.
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