calebmadrigal / Fouriertalkoscon
Presentation Materials for my "Sound Analysis with the Fourier Transform and Python" OSCON Talk.
Stars: ✭ 244
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Fouriertalkoscon
Tutorials
Ipython notebooks for math and finance tutorials
Stars: ✭ 654 (+168.03%)
Mutual labels: jupyter-notebook, math
Mathy
Tools for using computer algebra systems to solve math problems step-by-step with reinforcement learning
Stars: ✭ 79 (-67.62%)
Mutual labels: jupyter-notebook, math
Machine learning basics
Plain python implementations of basic machine learning algorithms
Stars: ✭ 3,557 (+1357.79%)
Mutual labels: jupyter-notebook, ipynb
Jupytext.vim
Vim plugin for editing Jupyter ipynb files via jupytext
Stars: ✭ 142 (-41.8%)
Mutual labels: jupyter-notebook, ipynb
Pynamical
Pynamical is a Python package for modeling and visualizing discrete nonlinear dynamical systems, chaos, and fractals.
Stars: ✭ 458 (+87.7%)
Mutual labels: ipynb, math
Show ast
An IPython notebook plugin for visualizing ASTs.
Stars: ✭ 76 (-68.85%)
Mutual labels: jupyter-notebook, ipynb
In simple english
Small projects to clarify big concepts
Stars: ✭ 140 (-42.62%)
Mutual labels: jupyter-notebook, math
Data Science Hacks
Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.
Stars: ✭ 273 (+11.89%)
Mutual labels: jupyter-notebook, ipynb
Tutorials
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Stars: ✭ 204 (-16.39%)
Mutual labels: jupyter-notebook, math
Notebooks Statistics And Machinelearning
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
Stars: ✭ 270 (+10.66%)
Mutual labels: jupyter-notebook, ipynb
Python intro
Jupyter notebooks in Russian. Introduction to Python, basic algorithms and data structures
Stars: ✭ 538 (+120.49%)
Mutual labels: jupyter-notebook, ipynb
Training Material
A collection of code examples as well as presentations for training purposes
Stars: ✭ 85 (-65.16%)
Mutual labels: jupyter-notebook, math
Alpha Mind
quantitative security portfolio analysis. The analysis pipeline including data storage abstraction, alpha calculation, ML based alpha combining and portfolio calculation.
Stars: ✭ 171 (-29.92%)
Mutual labels: jupyter-notebook, math
Functional intro to python
[tutorial]A functional, Data Science focused introduction to Python
Stars: ✭ 228 (-6.56%)
Mutual labels: jupyter-notebook, ipynb
Mozart
An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.
Stars: ✭ 241 (-1.23%)
Mutual labels: jupyter-notebook
Pytorch Vgg Cifar10
This is the PyTorch implementation of VGG network trained on CIFAR10 dataset
Stars: ✭ 243 (-0.41%)
Mutual labels: jupyter-notebook
Mirnet Tfjs
TensorFlow JS models for MIRNet for low-light image enhancement.
Stars: ✭ 145 (-40.57%)
Mutual labels: jupyter-notebook
FourierTalkOSCON
Presentation Materials for my Sound Analysis with the Fourier Transform and Python OSCON 2013 Talk.
Link to this: http://tinyurl.com/fourierpython
Presentation Index
- 01_Introduction.ipynb
- 02_NatureOfWaves.ipynb
- 03_FourierTransform.ipynb
- 04_WaveDeconvolution.ipynb
- 05_RotationWithE.ipynb
- 06_FFTInPython.ipynb
- 07_SeeingSound.ipynb
- 08_STFT.ipynb
- 09_AudioFiltering.ipynb
- 10_Conclusion.ipynb
To run locally, you must use this command to run ipython notebook: ipython notebook --pylab inline
You will also need to install these python libraries (along with their C dependencies):
- numpy
- scipy
- matplotlib
- ipython
- scikits.audiolab
To record audio on your laptop, you can use sox (note that rec is a commnad installed with sox). Here are 2 useful sox commands
-
rec -r 44100 -c 2 -b 16 A4.wav- records at 44100 samples per sec, 2 channels, and 16 bits per sample
-
sox audio_2channels.wav audio_1channel.wav channels 1- converts from 2 channels to 1 channel
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].