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bayesian-machine-learning

Notebooks related to Bayesian methods for machine learning

bioconductor-workshop-2

blog

A collection of resources and Jupyter notebooks from my blog.

brian2

Brian is a free, open source simulator for spiking neural networks.

cognitive-modelling

Simulating Neuro-Biological Systems

covid-19

A collection of work related to COVID-19

datasciencepython

common data analysis and machine learning tasks using python

decision-trees-for-knowledge-discovery

Understand and modelize the structure behind your data with Decision Trees

dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

du_bigdata_hw5_matplotlib-pyber

* You must use the Pandas Library and the Jupyter Notebook. * You must use the Matplotlib library. * You must include a written description of three observable trends based on the data. * You must use proper labeling of your plots, including aspects like: Plot Titles, Axes Labels, Legend Labels, X and Y Axis Limits, etc. * Your scatter plots must include [error bars](https://en.wikipedia.org/wiki/Error_bar). This will allow the company to account for variability between mice. You may want to look into [`pandas.DataFrame.sem`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.sem.html) for ideas on how to calculate this. * Remember when making your plots to consider aesthetics! * Your legends should not be overlaid on top of any data. * Your bar graph should indicate tumor growth as red and tumor reduction as green. It should also include a label with the percentage change for each bar. You may want to consult this [tutorial](http://composition.al/blog/2015/11/29/a-better-way-to-add-labels-to-bar-charts-with-matplotlib/) for relevant code snippets. * See [Starter Workbook](Pymaceuticals/pymaceuticals_starter.ipynb) for a reference on expected format. (Note: For this example, you are not required to match the tables or data frames included. Your only goal is to build the scatter plots and bar graphs. Consider the tables to be potential clues, but feel free to approach this problem, however, you like.) ## Hints and Considerations * Be warned: These are very challenging tasks. Be patient with yourself as you trudge through these problems. They will take time and there is no shame in fumbling along the way. Data visualization is equal parts exploration, equal parts resolution.

github-cheat-sheet

A list of cool features of Git and GitHub.

hyperopt-keras-cnn-cifar-100

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task. Updated version here: https://github.com/Vooban/Hyperopt-Keras-CNN-CIFAR-100

keras

Deep Learning for humans

keras-tensorflow-playground

Learning about keras and tensorflow for deep learning.

keras-vis

Neural network visualization toolkit for keras

learning-to-learn

Learning to Learn in TensorFlow

lm-snn

Using spiking neurons and spike-timing-dependent plasticity to classify the MNIST handwritten digits.

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

machine_learning

Python coded examples and documentation of machine learning algorithms.

makeyourownneuralnetwork

Code for the Make Your Own Neural Network book

muffin-cupcake

classifying muffin and cupcake recipes using support vector machines

nasa-latex-docs

Official Documentation:

nengo

A Python library for creating and simulating large-scale brain models

nengo-detailed-neurons

Enable Nengo to use neuron models simulated in NEURON.

netpyne

A python package to facilitate the development of biological neuronal networks in NEURON

nrn

NEURON Simulator. (iv required for the GUI)

pandas-ml

pandas, scikit-learn, xgboost and seaborn integration

pandas_exercises

Practice your pandas skills!

predict-if-salary-is-over-50k-with-keras

Predict whether income exceeds $50K/yr based on census data of the "Adult Dataset". Also known as "Census Income" dataset.

predictive-modelling-using-stepwise-eliminaton-method

Predictive modelling of miles per gallon and critically evaluating the step-wise elimination method.