Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look b
Python Data Science Essentials [source code]
โ Scribed by Alberto Boschetti, Luca Massaron
- Publisher
- Packt
- Year
- 2016
- Tongue
- English
- Edition
- 2nd
- Category
- Library
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas
NumPy's fast operations and computations -- Matrix operations -- Slicing and indexing with NumPy arrays -- Stacking NumPy arrays -- Summary -- Chapter 3: The Data Pipeline -- Introducing EDA -- Building new features -- Dimensionality reduction -- The covariance matrix -- Principal Component Analysis
NumPy's fast operations and computations -- Matrix operations -- Slicing and indexing with NumPy arrays -- Stacking NumPy arrays -- Summary -- Chapter 3: The Data Pipeline -- Introducing EDA -- Building new features -- Dimensionality reduction -- The covariance matrix -- Principal Component Analysis
NumPy's fast operations and computations -- Matrix operations -- Slicing and indexing with NumPy arrays -- Stacking NumPy arrays -- Summary -- Chapter 3: The Data Pipeline -- Introducing EDA -- Building new features -- Dimensionality reduction -- The covariance matrix -- Principal Component Analysis