Rishi Jain skycreeper2000
skycreeper2000
/ pg-pong.py
Created
September 8, 2019 16:45
— forked from karpathy/pg-pong.py
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
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| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |
skycreeper2000
/ Q-Table Learning-Clean.ipynb
Created
February 2, 2019 02:15
— forked from awjuliani/Q-Table Learning-Clean.ipynb
Q-Table learning in OpenAI grid world.
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skycreeper2000
/ softmax.ipynb
Created
January 28, 2019 20:56
— forked from awjuliani/softmax.ipynb
A simple ipython notebook that walks through the creation of a softmax regression model using MNIST dataset.
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skycreeper2000
/ solarSplines.R
Created
February 20, 2017 05:33
— forked from dickoa/solarSplines.R
A R version of the Python script for splines interpolation kindly provided by StormMiner. The code is a straight conversion thus not optimized but it works.
Have fun,
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| require(ncdf4) | |
| loadMesonetData <- function(filename, stationFilename = "station_info.csv") { | |
| data <- read.csv(file.path(data_path, filename)) | |
| station_data <- read.csv(file.path(data_path, stationFilename)) | |
| list(data = data[,-1], dates = data[,1], station_data = station_data) | |
| } | |