Python Jupyter-IPython Notebook Training - Advanced

Jupyter-IPython Notebook Training - Advanced

Catalog: Python
Short name: JPN - Advanced
Course start date: 2024-07-02
Paystack

Description

The I Python Notebook is now known as the Jupiter Notebook. It is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media. For more details on the Jupyter Notebook, please see the Jupyter website. IPython Notebook is a web-based interactive computational environment for creating IPython notebooks. This training is a practical approach to learn Python in such a way that will advance your career and increase your knowledge.


Through this training we shall be exploring Built in Functions, JavaScript and HTML rendering, Using JavaScript Widgets, Creating a Kernel in IPython, Automated Unit Testing, Understanding JSON and converting notebooks, Interactive Piano Widget and many other such concepts.


Few of the highlights of the training included are as follows:


How the Notebook Works

Ipython Magic Commands

Creating your own ipython kernel

Automation and Interactive Widgets

(Duration:- 7h 6m)

Sections

General
0 activities

Built in Functions
Java Script and HTML Rendering
Using Java Script Widgets
Using Java Script Widgets Continues
CSV Magic
More on CSV Magic
IPython Configuration System
Magic Commands
Creating a Kernel in IPython
Creating a Kernel in Ipython Continues
Do Execute Function
Automated Unit Testing
Automated Unit Testing Continues
Understanding JSON
Converting Notebooks
IPython NB Convert
Interactive Piano Widget
Interactive Piano Widget Continues
Set CSS Attribute Error
Creating JavaScript Spreadsheet Editor
Creating JavaScript Spreadsheet Editor Continues
Update Function
Data Frame Self
Processing Real Time Webcam Images
More on Webcam Images
Add Event Lister
Optimizing and Profiling Code Functions
Premature Optimization
Profiling Code Line by Line
Understanding Operation of NumPy Arrays
Processing NumPy Arrays with Memory Mapping
Cpython and Concurrent Programming
Numba Computing
Numba Computing Continues
Working Faster with Numba
Working Faster with Numexpr
Writing C Libraries in Python
Rebuild Project
Accelerating Python code with Cython
Load ext Cython
Combining Python with C
Combining Python with C Continues
Ray Tracer Example
Different Normalize Function
Asynchronous Parallel Computing
Asynchronous Parallel Computing Continues
Parallel Computing with Multiple Clusters
Advanced Visualization with Prettyplotlib
Dynamic Numerical Computing with Julia
More on Computing with Julia
Gadfly Plotting
Julia - Add PyPlot
Message Passing Interface
Numpy vs Numba JIT Computation
Using Seaborn for Statistical plotting
Plotting graphs with D3 Javascript
Plotting graphs with D3 Javascript Continues
Course Certificate

Secure Video
57
Certificate
1
Cost: 5000