• deploying a Machine Learning Model created with Python
• Please do ⭐ the repository, if it helped you in anyway.
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()
from xgboost import XGBRegressor
from sklearn.ensemble import RandomForestRegressor
from sklearn.tree import DecisionTreeRegressor
from sklearn.linear_model import LinearRegression
To run tests, run the following command
python app.py
Data 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