Data are thus no longer just information, but rather a resource with a huge economic value that is growing exponentially.

Data science, Big Data, Artificial Intelligence, Machine learning, and Deep Learning are the most popular tech buzzwords nowadays and this scenario is shaping a range of new professionals, known as Data Scientists, who are one of the most in-demand profiles. If you are willing to understand more, this book is here to guide you.

Data comes in different forms, but at an advanced level, it exists in three major categories. That is structured, semi-structured, and unstructured. Data scientists are experts responsible for gathering, analyzing, and interpreting large amounts of data to help businesses and organizations. Throughout all the chapters in this book, you are going to learn what the best data scientists know about Data analytics, Machine learning, big data, data mining, and statistics. Since Data Science is a multidisciplinary field, this book covers every critical concept that you must know to become a Professional Data Scientist.

Machine Learning uses the basics of Python programming language. Python is easy to learn and supports compelling typing. Python programs are very ‘natural’ in that it is easy to understand and read them (thanks to the exclusion of braces and semicolons). Python programming language can run on any computer platform, ranging from Linux to Windows to Solaris, and Macintosh etcetera. The simplicity nature of Python is what makes it accessible and a perfect choice for computer programmers.

By reading Data Science from Scratch you will discover:

Why Data Science and other new technologies are crucial today;Interesting background information about what you need to become a Data Scientist;Which are the most important activities in Data Analysis;Several tips about the data visualization and the processing;Several Tools and techniques used in Data Science and in other technologies such as Artificial Intelligence, Machine Learning, Big Data;Practical applications;

And much, much more...

This book will explore the field of data science using data and its structure. Also, it will describe high-level processes that one uses to change data into value. You know that Data Science is a process. However, this does not mean that it lacks creativity. When you move into stages of processing data, from analyzing data sources to machine learning, and finally, data visualization - you will start to see that complicated steps are involved in working with raw data.