jkotra

import mxnet as mx
from mxnet import nd, gluon, autograd
from mxnet.gluon import nn
import mxnet.ndarray as F

class Net(gluon.Block):
    def __init__(self, **kwargs):
        super(Net, self).__init__(**kwargs)
        with self.name_scope():
            

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#include <iostream>
#include <fstream>
#include <string>
#include <array>

using namespace std;

class Cycling{
private:
    float place_finished;

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#include <iostream>

using namespace std;

void gen_prime(int limit);

int main() {

    int limit;
    cout << "generate prime numbers upto:";

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LogoNet

Logonet is a convolutional neural network model to detect brand logo in the given input image.

it can detect the following brand logo's: (updated - 21/10/2018)

['ups','dhl','fedex','aldi','cocacola','mcdonalds']

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parms = {'max_depth': 8,'learning_rate':0.07, 'eta': 0.03, 'subsample': 1, 'colsample_bytree': 0.8, 'objective': 'reg:linear', 'eval_metric': 'rmse', 'silent': 0}
reg = xgb.XGBRegressor(parms=parms,n_jobs=6)
reg = xgb.train(parms, dtrain, num_boost_round=500)