"What I cannot create, I do not understand", Feynman (1988)
This repository aims to collect useful bits of information/building blocks (e.g. code, tutorial, etc.) for machine learning, speech analysis, Python, TensorFlow, Praat, Matlab and so on.
Since the collections of code and tutorials are primarily written for the purpose of studying on my own, there might be some errors or bugs. It would be appreciated if you let me know any of them.
This collection will be updated slowly, but steadily. Credits go to all the developers/researchers/coders that I've referred to.
- Gradient Descent: Basic Gradient Descent algorithm and its implementation using Matlab
- Linear Regression: Linear regression example using Tensorflow on Python (e.g. predicting the number of theft from the number of fire in the city)
- Logistic Regression: Logistic regression example using Tensorflow on Python (e.g. Iris type classification)
- Multilayer Perceptron (ANN): Example of multilayer perceptron (Vanila Neural Network) code
- RNN-LSTM: RNN, LSTM based code examples; e.g. simple character-level language modeling, sinewave predictor, etc.
- Github: Useful commands and notes for Github
- Jupyter: Useful options and settings for Jupyter environment
- Python: Python code and tutorial; tips and essential code
- Tensorflow: Tips and notes for machine learning implementation using Tensorflow