IPython and Jupyter Notebook In Practice: 3-in-1

Use IPython and Jupyter Notebook to sharpen your skills for your data analysis and visualization tasks

Created by: Packt Publishing
Tech Knowledge in Motion

What Will I Learn?

• Use the IPython notebook to modernize the way you interact with Python
• Perform highly efficient computations with NumPy and Pandas
• Optimize your code using parallel computing and Cython
• Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments
• Visualize data and create interactive plots in the Jupyter Notebook
• Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more
• Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn)
• Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV
• Simulate deterministic and stochastic dynamical systems in Python
• Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory

Requirements

• Knowledge of Python is required, whereas no knowledge of IPython is necessary.

Target audience

• This course is for Python developers, data scientists, and analysts who use Python as a scripting language or for software development, and are interested in learning IPython and Jupyter Notebook for numerical computing and data science.