https://github.com/akash1070/predicting-compressive-strength-of-concrete-model

Predicting Compressive Strength of Concrete
https://github.com/akash1070/predicting-compressive-strength-of-concrete-model

adaboost-regressor bagging-regressor decisiontreeregressor kneighborsregressor python3 svm-model xgboost

Last synced: 22 days ago
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Predicting Compressive Strength of Concrete

• Host: GitHub
• URL: https://github.com/akash1070/predicting-compressive-strength-of-concrete-model
• Owner: Akash1070
• Created: 2022-09-16T09:39:17.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-09-19T15:46:43.000Z (over 2 years ago)
• Last Synced: 2024-04-05T11:45:28.366Z (9 months ago)
• Topics: adaboost-regressor, bagging-regressor, decisiontreeregressor, kneighborsregressor, python3, svm-model, xgboost
• Language: Jupyter Notebook
• Homepage:
• Size: 1.57 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# **Predicting Compressive Strength of Concrete**

![Python 3.6](https://img.shields.io/badge/Python-3.6-brightgreen.svg)

![pyforest](https://img.shields.io/badge/Library-pyforest-red.svg)

![Pandas](https://img.shields.io/badge/Library-Pandas-orange.svg)

![seaborn](https://img.shields.io/badge/Library-seaborn-blue.svg)

![matplotlib.pyplot](https://img.shields.io/badge/Library-matplotlib.pyplot-violet.svg)

![Numpy](https://img.shields.io/badge/Library-Numpy-blue.svg)

• deploying a ___Machine Learning Model___ created with ___Python___ 

## Authors

- [@Akash Kumar Jha](https://github.com/Akash1070)

## Deployment

    1. Data Extraction

    2. Exploratory Data Analysis(EDA)

    3. Feature Engineering

    4. Model Building and Tuning

   

## Installation

To install the libraries used in this project. Follow the 

below steps:

```bash

!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 pydot

```

    

## Running Flask Api

To run tests, run the following command

```bash

  python app.py

```

## 🚀 About Me

Data Scientist Enthusiast | Petroleum Engineer Graduate | Solving Problems Using Data 

# Hi, I'm Akash! 👋

## 🔗 Links

[![github](https://img.shields.io/badge/github-000?style=for-the-badge&logo=ko-fi&logoColor=white)](https://github.com/Akash1070)

[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/akashkumar107/)

## Tech Stack

![Logo](https://businesstoys.in/assets/programs/full-stack-data-science-professional-program/tools.png)

## Other Me

👩‍💻 I’m interested in Petroleum Engineering

🧠 I’m currently learning Data Scientist | Data Analytics | Business Analytics

👯‍♀️ I’m looking to collaborate on Ideas & Data

## 🛠 Skills

1. Data Scientist

2. Data Analyst

3. Business Analyst

4. Machine Learning 

## Future Plans 

⚡️ 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