Название: Python for Data Science: The Ultimate Beginners' Guide to Data Science, Predictive Analytics, Statistics, and Machine Learning Автор: Zed Fast
Издательство: Independently published
Год: 2019
Страниц: 131
Язык: английский
Формат: pdf, azw3, epub
Размер: 10.1 MB
What would it feel like if you could know your business decisions were accurate, and that they would always be successful? If you want to make your business more effective using all the data you have then read more.
To start out this guidebook, we are going to take a look at what data science is all about, why it is important, and why we would want to work with this process in the first place as well. We will then take some time in order to learn the lifecycle of data science, and how we need to go through a series of steps like the finding the right data, preparing the data, coming up with the right model, and more. All of this and more will be discussed in this guidebook so that you can go from start to finish with your own data science project.
Then we are going to spend some time taking a look at the basics that come with the Python language, and how we are able to use this to help with our data science project. There are a lot of great coding languages out there that we are able to work with when it is time to handle data science, but many agree that the power, the libraries, and the ease to use and learn of Python make it one of the best choices to handle with this idea. We will also spend some time looking at a few of the libraries that are going to work with when it comes to Python, including NumPy and its arrays, Seaborn, and Matplotlib to get all of the work done in no time.
You will learn:
What data science is all about and why so many companies are using it to give them a competitive edge.
Why Python language is a great option to handle your data science project.
The steps that come with a data science project.
Where machine learning can fit into the world of data science.
What predictive analytics is all about and why this works with data science as well.
Best libraries for data science, including Matplotlib, Seaborn, and the NumPy arrays.
Using data visuals to take all of that information that we have gathered up already and use it to help us really understand the insights data science gives us.
Some of the real-life applications of data science and why you need to consider using this for your needs as well.
Even if you never used data science, learning it is easier than it looks, you just need the right guidance. This practical guide can bring your business to the front of competition.
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