• deploying a Machine Learning Model created with Python
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:
!pip install pyforest
from pyforest import*
lazy_imports()
!pip install graphviz
!pip install pydot
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import itertools
%matplotlib inline
from sklearn.ensemble import AdaBoostRegressor
from sklearn.neighbors import KNeighborsRegressor
from sklearn.ensemble import BaggingRegressor
from sklearn.svm import SVR
import xgboost as xgb
from sklearn.tree import DecisionTreeRegressor
from sklearn.tree import export_graphviz
from sklearn.externals.six import StringIO
from IPython.display import Image
import graphviz
import pydotTo 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
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- 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