Название: Data Science from Scratch with Python: A Step By Step Guide for Beginner's and Faster Way To Learn Python In 7 Days & NLP using Advanced (Including Programming Interview Questions) Автор: Richard Wilson
Издательство: Amazon.com Services LLC
Год: 2019
Страниц: 189
Язык: английский
Формат: pdf, azw3
Размер: 10.1 MB
Data Science is present in our lives: newspapers talk about viral news, companies look for data scientists, businesses offer us personalized offers based on our customs and we grease the system by offering free personal information from our social networks, Internet searches and even from smart devices to control our daily physical activity.
This book presents the knowledge and technologies that will allow us to participate in this new era of information, governed by Big Data and machine learning, the life of the data is analyzed step by step, showing how to obtain it, store it, process it, visualize it, and draw conclusions from it: that is, show the data analysis as it is: a fascinating area, It requires many hours of careful work. Likewise, the Python programming language is analyzed, the most used in data Science due to the multitude of libraries that it facilitates, but is not limited to the standard, but presents current technologies that, with Python as an interface, will allow scaling the size of the data to the maximum. Therefore, our journey with the data will take us, for example, to know the MongoDB database and the Spark processing environment.
What languages should be learned?
In reality, as any initiate knows, in programming the choice of one language or another is always complicated. In this election they intervene from technical or formative factors to simple personal preferences. What is clear is that there are some languages more popular than others.
The three musketeers of Data Science: SQL, R, Python. Although common sense tells us that each language is better for certain things, in practice there is a certain rivalry. Personally, I use R but I usually recommend Python. Not only because it is prettier, but because it is
multipurpose and that is always an advantage.
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