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 fundamentalsthat are sometimes skipped
over in the rush to be productive. Some knowledge of object-oriented programming will make
learning easier.
