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Data Science From Scratch: Ultimate Guide To Master Data Mining And Data-Analytic From Linear Algebra And Statistics To Practical Examples Of Neural Networks ... In Python
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Do you want to know all about data science? Do you really want to understand why it is the future in all the most demanding job?
The truth Data science is the need of the hur. Over the last few years, it has changed the concept of technology. It is adding value to every model of business by using deep learning and statistics. Technological benefits of data science cannot also be ignored.
The demand for data science is increasing rapidly. The basic reason behind this is the massive boom in the data generated and retained by the companies. Also known as “big data”, data scientists make the best use of this available information and figure out their best use.
The team of data scientists also help in generating a good amount of analytics from the information available. This information brings clarity to people on how to interact with the web and are the foundations on which most of the critical business strategies rest. The demand for the data scientists is gradually increasing and so there must be proper learning resources for them to cultivate their knowledge.
Data Science from Scratch, Ultimate Guide to Master Data Mining and data-Analytic from Linear Algebra and Statistics to Practical Examples of Neural Networks and Machine Learning in Python.
A data scientist has the following tasks to
Analyse data
Modelling/statistics
Engineering/prototyping
A lot of data is available in every organization. All of them are not that easy to format. A data scientist’s job mainly revolves around formatting these data, keeping in mind some set of rules.
The goal of this book is The book provides a perfect insight into data science from the very scratch. It clearly explains the difference between data science and big data, explaining the concept of big data very concisely and clearly. Operations on data are also very clearly explained in this eBook.
The book also stresses on Ultimate Guide to Master Data Mining and data-Analytic from Linear Algebra and Statistics to Practical Examples of Neural Networks and Machine Learning in Python.
You will also
What is big data
Difference between Data Science and big data
Operations on data
munging, cleaning, manipulating and rescaling data
basic linear algebra with exercises
Statistics and basic concept
Decision tree and how to use them
Languages required for data science
Basics of python
Neural network and what to use for (with examples)
Machine learning (with examples)
&
Do you want to know all about data science? Do you really want to understand why it is the future in all the most demanding job?
The truth Data science is the need of the hur. Over the last few years, it has changed the concept of technology. It is adding value to every model of business by using deep learning and statistics. Technological benefits of data science cannot also be ignored.
The demand for data science is increasing rapidly. The basic reason behind this is the massive boom in the data generated and retained by the companies. Also known as “big data”, data scientists make the best use of this available information and figure out their best use.
The team of data scientists also help in generating a good amount of analytics from the information available. This information brings clarity to people on how to interact with the web and are the foundations on which most of the critical business strategies rest. The demand for the data scientists is gradually increasing and so there must be proper learning resources for them to cultivate their knowledge.
Data Science from Scratch, Ultimate Guide to Master Data Mining and data-Analytic from Linear Algebra and Statistics to Practical Examples of Neural Networks and Machine Learning in Python.
A data scientist has the following tasks to
Analyse data
Modelling/statistics
Engineering/prototyping
A lot of data is available in every organization. All of them are not that easy to format. A data scientist’s job mainly revolves around formatting these data, keeping in mind some set of rules.
The goal of this book is The book provides a perfect insight into data science from the very scratch. It clearly explains the difference between data science and big data, explaining the concept of big data very concisely and clearly. Operations on data are also very clearly explained in this eBook.
The book also stresses on Ultimate Guide to Master Data Mining and data-Analytic from Linear Algebra and Statistics to Practical Examples of Neural Networks and Machine Learning in Python.
You will also
What is big data
Difference between Data Science and big data
Operations on data
munging, cleaning, manipulating and rescaling data
basic linear algebra with exercises
Statistics and basic concept
Decision tree and how to use them
Languages required for data science
Basics of python
Neural network and what to use for (with examples)
Machine learning (with examples)
&
175 pages, Kindle Edition
Published July 25, 2019
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