Normal view MARC view ISBD view

Data science fundamentals for Python and Mongodb

By: Paper, David.
Material type: materialTypeLabelBookPublisher: New York Apress Media 2018Description: xiii, 214 p.: ill. Includes index.ISBN: 9781484240182.Subject(s): Python - Computer program language | MongoDB | Data mining | Computer science | Databases | Information technologyDDC classification: 006.312 Summary: Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms. The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained. Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky” at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced. What You'll Learn Prepare for a career in data science Work with complex data structures in Python Simulate with Monte Carlo and Stochastic algorithms Apply linear algebra using vectors and matrices Utilize complex algorithms such as gradient descent and principal component analysis Wrangle, cleanse, visualize, and problem solve with data Use MongoDB and JSON to work with data Who This Book Is For The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier. https://www.apress.com/gp/book/9781484235966
List(s) this item appears in: Data Science
Tags from this library: No tags from this library for this title. Log in to add tags.
    average rating: 0.0 (0 votes)
Item type Current location Item location Collection Call number Status Date due Barcode
Books Vikram Sarabhai Library
General Stacks
Slot 105 (0 Floor, West Wing) Non-fiction 006.312 P2D2 (Browse shelf) Available 201179

Table of Contents

1. Introduction
2. Monte Carlo Simulation and Density Functions
3. Linear Algebra
4. Gradient Descent
5. Working with Data
6. Exploring Data

Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms.
The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained.
Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky” at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced.
What You'll Learn
Prepare for a career in data science
Work with complex data structures in Python
Simulate with Monte Carlo and Stochastic algorithms
Apply linear algebra using vectors and matrices
Utilize complex algorithms such as gradient descent and principal component analysis
Wrangle, cleanse, visualize, and problem solve with data
Use MongoDB and JSON to work with data
Who This Book Is For
The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier.

https://www.apress.com/gp/book/9781484235966

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha