Description
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.
Tagline
Primer into the multidisciplinary world of Data Science
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
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
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.
Tagline
Primer into the multidisciplinary world of Data Science
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
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
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.
