Data Science Fundamentals for Python and MongoDB, 1st ed.
Auteur : Paper David
- 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
Date de parution : 05-2018
Ouvrage de 214 p.
15.5x23.5 cm
Thèmes de Data Science Fundamentals for Python and MongoDB :
Mots-clés :
Data Science; Simulation; Monte Carlo Simulation; Linear Algebra; Vector and Matrix Math; Stochastic Simulation; Randomness; Gradient Descent; Data Wrangling; Data Cleansing; Heat Map; MongoDB; NoSQL; JSON; Python Pandas Library; Python NumPy Library; Data Visualization; Uniform Distribution; Normal Distribution