Data Science Fundamentals for Python and MongoDB

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.