1. Data Extraction
2. Exploratory Data Analysis(EDA)
3. Feature Engineering
4. Model Building and Tuning
To install the libraries used in this project. Follow the below steps:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import pickle
%matplotlib inline
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import StandardScaler
To run tests, run the following command
python app.pyData Scientist Enthusiast | Petroleum Engineer Graduate | Solving Problems Using Data
👩💻 I’m interested in Petroleum Engineering
🧠 I’m currently learning Data Scientist | Data Analytics | Business Analytics
👯♀️ I’m looking to collaborate on Ideas & Data
- Data Scientist
- Data Analyst
- Business Analyst
- Machine Learning
⚡️ Looking forward to help drive innovations into your company as a Data Scientist
⚡️ Looking forward to offer more than I take and leave the place better than i found