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
- Length: 189 pages
- Edition: 1
- Language: English
- Publication Date: 2019-09-10
- ISBN-10: B07XLC99Q4
- Sales Rank: #37481 (See Top 100 Books)
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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.
In this book, you will discover:
- What is a data scientist?
- What languages should be learned?
- The three musketeers of Data Science
- Python introduction
- Languages do you need to learn for data science
These are some of the topics covered in this book:
- Machine Learning Algorithms
- K NN – Nearest Neighbor Method
- SVC – Support vector machine
- Mathematics for Data Analysis
- Working with Threads in Python
- Working with processes in Python
The book contains detailed examples of how to perform the different tasks in Python; and in addition, for the convenience of the reader of the included fragments, the access of the readers to a repository where they will find the code ready to be executed is facilitated. Also each chapter presents recommended readings to be able to deepen in those aspects that are more interesting. We invite you to immerse yourself in the exciting world of data Science in Python and explore the mysteries of Big Data and machine learning!
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