Название: Data Science for Business Professionals: A Practical Guide for BeginnersАвтор: Probyto Data Science and Consulting Pvt. Ltd.
Издательство: BPB Publications
Год: 2020
Страниц: 366
Язык: английский
Формат: epub
Размер: 12.7 MB
Primer into the multidisciplinary world of Data Science.
The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.
Machine Learning (ML) is a subset of Artificial intelligence (AI) algorithms. It makes the software applications more efficient and accurate in processing the historical data to predict the outcomes of future data. A notable point is machine learning algorithms try to get the output without explicitly programmed. The flow of machine learning is to build the algorithms with the input of data from the past and near future and use the standard statistical analysis methods to find the new outcomes whenever the new data becomes comes into the algorithm. Increasing the input data exposure to the algorithms during the training phase will make the algorithm performance better. This process of processing the input data is also known as the learning of the Machine Learning algorithm.
What will you learn:
Understand the multi-disciplinary nature of Data Science
Get familiar with the key concepts in Mathematics and Statistics
Explore a few key ML algorithms and their use cases
Learn how to implement the basics of Data Pipelines
Get an overview of Cloud Computing & DevOps
Learn how to create visualizations using Tableau
Key Features:
Explore and use the key concepts of Statistics required to solve data science problems
Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app
Learn how to build Data Science solutions with GCP and AWS
Who this book is for:
This book is ideal for Data Science enthusiasts who want to explore various aspects of Data Science. Useful for Academicians, Business owners, and Researchers for a quick reference on industrial practices in Data Science.
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