Data Science From Scratch Using R
Step by Step Guide For Beginners
Nonfiction, Computers, Advanced Computing, Engineering, Neural Networks, Computer Engineering, Programming, Data Modeling & Design
| Author: | Alain Kaufmann | ISBN: | 9781643160726 |
| Publisher: | Data Sciences | Publication: | May 26, 2018 |
| Imprint: | Language: | English |
| Author: | Alain Kaufmann |
| ISBN: | 9781643160726 |
| Publisher: | Data Sciences |
| Publication: | May 26, 2018 |
| Imprint: | |
| Language: | English |
Are you thinking of learning more about Machine Learning using R?
The overall aim of this book is to give you an overview of the data science applications using R.
Data science is the practice of transforming data into knowledge, and R is the most popular open-source programming language used for data science. In our data-driven economy, this combination of skills is in extremely high demand, commanding significant increases in salary as it's revolutionizing the world around us. In this book, we will learn how to use the principles of data science and the R programming language to answer day-to-day questions about your data. As an overview of this course, first, we'll learn about the practice of data science and the R programming language. Then, we'll learn how to work with data to create descriptive statistics, data visualizations, and statistical models. Finally, we'll learn how to handle big data, make predictions with machine learning, and deploy our applications into production. By the end of this book, you'll have the skills necessary to use R and the principles of data science to transform your data into actionable insight.
Book Objectives
This book will help you:
- Have an appreciation for neural network and an understanding of their fundamental principles.
- Have an elementary grasp of neural network concepts and algorithms.
- Have achieve a technical background in artificial neural networks and also deep learning
Target Users
The book designed for a variety of target audiences. The most suitable users would include:
- Newbies in computer science techniques and data science
- Professionals in machine learning and social sciences
- Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way
- Students and academicians, especially those focusing on data science practical guide using R
Is this book for me?
If you want to smash Data Science from scratch, this book is for you. Little programming experience is required. If you already wrote a few lines of code and recognize basic programming statements, you’ll be OK.
Are you thinking of learning more about Machine Learning using R?
The overall aim of this book is to give you an overview of the data science applications using R.
Data science is the practice of transforming data into knowledge, and R is the most popular open-source programming language used for data science. In our data-driven economy, this combination of skills is in extremely high demand, commanding significant increases in salary as it's revolutionizing the world around us. In this book, we will learn how to use the principles of data science and the R programming language to answer day-to-day questions about your data. As an overview of this course, first, we'll learn about the practice of data science and the R programming language. Then, we'll learn how to work with data to create descriptive statistics, data visualizations, and statistical models. Finally, we'll learn how to handle big data, make predictions with machine learning, and deploy our applications into production. By the end of this book, you'll have the skills necessary to use R and the principles of data science to transform your data into actionable insight.
Book Objectives
This book will help you:
- Have an appreciation for neural network and an understanding of their fundamental principles.
- Have an elementary grasp of neural network concepts and algorithms.
- Have achieve a technical background in artificial neural networks and also deep learning
Target Users
The book designed for a variety of target audiences. The most suitable users would include:
- Newbies in computer science techniques and data science
- Professionals in machine learning and social sciences
- Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way
- Students and academicians, especially those focusing on data science practical guide using R
Is this book for me?
If you want to smash Data Science from scratch, this book is for you. Little programming experience is required. If you already wrote a few lines of code and recognize basic programming statements, you’ll be OK.
