ipython-books / Minibook 2nd Code
Code of the IPython Minibook, 2nd edition (2015)
Stars: ✭ 303
Labels
Projects that are alternatives of or similar to Minibook 2nd Code
Nuscenes Devkit
Devkit for the public 2019 Lyft Level 5 AV Dataset (fork of https://github.com/nutonomy/nuscenes-devkit)
Stars: ✭ 299 (-1.32%)
Mutual labels: jupyter-notebook
Spyder Notebook
Jupyter notebook integration with Spyder
Stars: ✭ 298 (-1.65%)
Mutual labels: jupyter-notebook
Python Seminar
Python for Data Science (Seminar Course at UC Berkeley; AY 250)
Stars: ✭ 302 (-0.33%)
Mutual labels: jupyter-notebook
Scikit Learn Videos
Jupyter notebooks from the scikit-learn video series
Stars: ✭ 3,254 (+973.93%)
Mutual labels: jupyter-notebook
Scipy2014 tutorial
Tutorial: Bayesian Statistical Analysis in Python
Stars: ✭ 299 (-1.32%)
Mutual labels: jupyter-notebook
Attention is all you need
Transformer of "Attention Is All You Need" (Vaswani et al. 2017) by Chainer.
Stars: ✭ 303 (+0%)
Mutual labels: jupyter-notebook
Capsule net pytorch
Readable implementation of a Capsule Network as described in "Dynamic Routing Between Capsules" [Hinton et. al.]
Stars: ✭ 301 (-0.66%)
Mutual labels: jupyter-notebook
Pyspark Tutorials
Code snippets and tutorials for working with social science data in PySpark
Stars: ✭ 300 (-0.99%)
Mutual labels: jupyter-notebook
Reactors
Content for Microsoft Reactor Workshops
Stars: ✭ 299 (-1.32%)
Mutual labels: jupyter-notebook
Car Finding Lane Lines
Finding Lane Lines using Python and OpenCV
Stars: ✭ 299 (-1.32%)
Mutual labels: jupyter-notebook
Basic Mathematics For Machine Learning
The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI
Stars: ✭ 300 (-0.99%)
Mutual labels: jupyter-notebook
Handwritten Text Recognition For Apache Mxnet
This repository lets you train neural networks models for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.
Stars: ✭ 300 (-0.99%)
Mutual labels: jupyter-notebook
Ai notes
machine learning/artificial intelligence notes
Stars: ✭ 301 (-0.66%)
Mutual labels: jupyter-notebook
Adaptiveattention
Implementation of "Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning"
Stars: ✭ 303 (+0%)
Mutual labels: jupyter-notebook
Pydataroad
open source for wechat-official-account (ID: PyDataLab)
Stars: ✭ 302 (-0.33%)
Mutual labels: jupyter-notebook
IPython minibook, second edition
This repository contains all the code examples as IPython notebooks.
Table of contents
1. Getting started with IPython
- 1.1. What are Python, IPython, and Jupyter?
- 1.2. Installing Python with Anaconda (Complete sample!)
- 1.3. Introducing the Notebook (Complete sample!)
- 1.4. A crash course on Python (Complete sample!)
- 1.5. Ten Jupyter/IPython essentials
- 1.6. Summary
2. Interactive data analysis with pandas
- 2.1. Exploring a dataset in the Notebook
- 2.2. Manipulating data
- 2.3. Complex operations
- 2.4. Summary
3. Numerical computing with NumPy
- 3.1. A primer to vector computing
- 3.2. Creating and loading arrays
- 3.3. Basic array manipulations
- 3.4. Computing with NumPy arrays (Complete sample!)
- 3.5. Summary
4. Interactive plotting and Graphical Interfaces
- 4.1. Choosing a plotting backend
- 4.2. matplotlib and seaborn essentials
- 4.3. Image processing
- 4.4. Further plotting and visualization libraries
- 4.5. Summary
5. High-performance and parallel computing
- 5.1. Accelerating Python code with Numba
- 5.2. Writing C in Python with Cython
- 5.3. Distributing tasks on several cores with IPython.parallel
- 5.4. Further high-performance computing techniques
- 5.5. Summary
6. Customizing IPython
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].