adesgautam

import gym
import numpy as np
import time
import pickle, os

env = gym.make('FrozenLake-v0')

with open("frozenLake_qTable.pkl", 'rb') as f:
	Q = pickle.load(f)

NNmultiClass.py

import os
import csv
import time
import sys
sys.path.append("C:/Users/dm/Documents/GaTech/ML/assn2/ABAGAIL/ABAGAIL.jar")
from func.nn.backprop import BackPropagationNetworkFactory
from shared import SumOfSquaresError, DataSet, Instance
from opt.example import NeuralNetworkOptimizationProblem
from func.nn.backprop import RPROPUpdateRule, BatchBackPropagationTrainer

spitis

AustinRochford

primaryobjects

library(caret)
library(doParallel)
library(reshape2)
library(ggplot2)

# Enable parallel processing.
cl <- makeCluster(detectCores())
registerDoParallel(cl)

# Load the MNIST digit recognition dataset into R