Eligijus112

Eligijus112

import pandas as pd 
from datetime import datetime
import numpy as np 
import re

# To datetime conversion 
def to_datetime(x: str) -> datetime:
    """
    Converts a string to a datetime object
    An example of the string is 2010-02-02 17:24:55

Eligijus112

import numpy as np
import pandas as pd

# Defining the function for distance calculation
def distance_calculation(df: pd.DataFrame) -> pd.DataFrame:
    """
    Calculates the distance between two points on the earth's surface.

    The distance is in meters
    """

Eligijus112

import pandas as pd 
from sklearn.preprocessing import OneHotEncoder
import numpy as np

# Defining the function for dummy creation 
def create_dummy(df: pd.DataFrame, dummy_var_list: list) -> Tuple:
    """
    Creates dummy variables for the variables in dummy_var_list

    Returns a tuple of the following

Eligijus112

# Deep learning 
import tensorflow as tf
import keras

# Memory tracking
from memory_profiler import profile

@profile
def create_model(
    input_size: int, 

Eligijus112

# Importing the feature engineering pipeline 
from utils import ft_engineering_pipeline

# Data wrangling
import pandas as pd

# Memory tracking
from memory_profiler import profile

# Command line arguments 

Eligijus112

import pandas as pd 
import numpy as np 
import keras

# Defining the class for the batches creation 
class DataGenerator(keras.utils.Sequence):
    def __init__(
        self, 
        csv_generator: pd.io.parsers.readers.TextFileReader,
        n_batches: int,

Eligijus112

# Data wrangling 
import pandas as pd

# Deep learning 
import tensorflow as tf
import keras 

# Import feature engineering functions
from utils import create_date_vars, distance_calculation, custom_transform