Derek Haile, May 23, 2020. — 978-1393466352.
The following chapters will discuss all of the different parts that you need to know to get started with your Data Science project. Many companies are interested in learning more about this process and what it can do for them figuring out what this all means and how this kind of process can propel us to the future with our smart decisions and more, can ensure that you are going to be successful when it is time to handle yourself in the future.
There are so many parts that come with a Data Science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this Data Science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your environment to get started with Data Science, and some of the best libraries that are out there to help us succeed with the use of Data Science and Python put to get
From there, we need to get into some of the details that come up when we are working on a Data Science project. We will look at how we can gather up some of the data we need, the importance of cleaning up all of that data and getting it to work where we would like, how to handle some of the NumPy arrays to get the work done, and the basics of working with data analysis in this process. The guidebook will also finish up with one final stop looking at some of the benefits of creating data visuals so that we can take all of the information and trends that we learned bout in the other chapters, and put them into a form that is easy to read through and comprehend.
We will then finish up with a good look at how to work with machine learning and what this can offer to us as well when it comes to programming in Python. There are so many different parts that come with machine learning, but we will quickly find that this is going to be the best place for us to learn more about the data we are exploring and can help us to create some of the algorithms that we need in this language.
Many businesses are able canwhen they work with data analysis for some of their needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.
There are plenty of books on this subject on the market, thanks again for choosing this one! Every effort was made to ensure it is full of as much useful information as possible, please enjoy it!
Chapter 1: What Is Data Science?
Chapter 2: How Can I Use Data Science?
Chapter 3: The Best Python Libraries for Data Science.
Chapter 4: Setting Up Your Virtual Environments for Data Science.
Chapter 5: The Importance of the NumPy Arrays.
Chapter 6: Gathering and Collecting Your Data.
Chapter 7: Loading and Preparing Your Dataset.
Chapter 8: Data Mining.
Chapter 9: Completing the Data Analysis.
Chapter 10: How Machine Learning Can Help.
Chapter 11: How to Work with Data Visualization.