sananand007

'''
Logistic Regression
'''
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, confusion_matrix, f1_score, roc_curve, precision_score, classification_report
lgmodel = LogisticRegression(max_iter=100, C=1e5)
lgmodel.fit(X_train, y_train)
ypred=lgmodel.predict(X_test)
print(lgmodel.score(X_train, y_train))
print(confusion_matrix(y_test,ypred))

sananand007

# Turn into classes using pd.cut()
df_train_filt2['Fareclass']=pd.qcut(df_train_filt2['Fare'], 4, labels=[1,2,3,4])
df_train_filt2['Ageclass']=pd.qcut(df_train_filt2['Age'], 5, labels=[1,2,3,4,5])
df_test_filt1['Fareclass']=pd.qcut(df_test_filt1['Fare'], 4, labels=[1,2,3,4])
df_test_filt1['Ageclass']=pd.qcut(df_test_filt1['Age'], 5, labels=[1,2,3,4,5])
df_train_filt2.drop(['Fare','Age'], axis=1, inplace=True)
df_test_filt1.drop(['Fare','Age'], axis=1, inplace=True)

# Get the encoding done to get rid of string columns that you cannot train
df_train_filt2=pd.get_dummies(df_train_filt2, columns=\

sananand007

# Get the Data and see the dataset
import os
import matplotlib.pyplot as plt
import pandas as pd
path=os.getcwd()
filepath=[]
for file in os.listdir(path):
    if 'csv' in file:filepath.append(path+"\\"+file)
for path in filepath:
    if "train" in path:df_train=pd.read_csv(path)

sananand007

# Now to fill up the NA values for Ages
mean_age=df_train_filt2['Age'].mean()
listofAgeind_=list(df_train_filt2[df_train_filt2['Age'].isna()==True].index)
list_of_ages=np.random.normal(mean_age, 10, len(listofAgeind_))

plt.plot(list_of_ages, linewidth=2, color='g', label='Age')
plt.show()
for (idx,age) in zip(listofAgeind_,list_of_ages):df_train_filt2.loc[idx, 'Age']=age
print(df_train_filt2.count())

sananand007

Running a Jupyter Instance using Amazon sagemaker

Loading the data using kaggle-cli

• Links
  • https://www.kaggle.com/general/6604
  • https://github.com/floydwch/kaggle-cli
  • [Downloading the files] https://stackoverflow.com/questions/7243750/download-file-from-web-in-python-3
• Kaggle Username and password :
• [email protected] | ********

sananand007

How to Login into the Jupyter Notebook through AWS and Conda Environment created in AWS :

Installing Anaconda on Ubuntu :

• refer : https://www.digitalocean.com/community/tutorials/how-to-install-the-anaconda-python-distribution-on-ubuntu-16-04

    - https://repo.continuum.io/archive/Anaconda3-5.1.0-Linux-x86_64.sh
       cd /tmp
    - curl -O https://repo.continuum.io/archive/Anaconda3-5.1.0-Linux-x86_64.sh
    - check the sha256sum: sha256sum Anaconda3-5.1.0-Linux-x86_64.sh

sananand007

Studying for a Tech Interview Sucks, so Here's a Cheat Sheet to Help

This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.

Data Structure Basics

###Array ####Definition:

• Stores data elements based on an sequential, most commonly 0 based, index.
• Based on tuples from set theory.