jkotra

from bs4 import BeautifulSoup
import csv
import requests

###################################
#       Jagadeesh Kotra           #
#       hello@jagadeesh.me        #
###################################

scrap = []

jkotra

from numpy import base_repr

def sum_of_digits(array):
    digit_sum = []

    for i in range(len(array)):
        x = [int(x) for x in str(array[i])]
        digit_sum.append(sum(x))
    return digit_sum

jkotra

train = train[train['fare_amount'] > 0]
train = train[train['pickup_longitude'] < -72]
train = train[(train['pickup_latitude'] > 40) & (train['pickup_latitude'] < 44)]
train = train[train['dropoff_longitude'] < -72]
train = train[(train['dropoff_latitude'] > 40) & (train['dropoff_latitude'] < 44)]
train = train[(train['passenger_count'] > 0) & (train['passenger_count'] < 10)]

#---#

jkotra

from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, Activation
from keras import optimizers
from keras import regularizers

model = Sequential()
model.add(Dense(128, activation='relu', input_dim=len(features)))
model.add(Dense(64))
model.add(Dense(1))

jkotra

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)

jkotra

jkotra

jkotra

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']

jkotra

jkotra