semvec/pypi-packages huggingface dataset:
example-package-Akalya 0.0.1
A small example package
Requires Python: >=3.7

<<<<<<< HEAD
# mle-training
=======
# mle-training
# Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data. 

The following techniques have been used: 

 - Linear regression
 - Decision Tree
 - Random Forest

## Steps performed
 - We prepare and clean the data. We check and impute for missing values.
 - Features are generated and the variables are checked for correlation.
 - Multiple sampling techinuqies are evaluated. The data set is split into train and test.
 - All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

## To excute the script
python < scriptname.py >
streamlit-custom-tabs 0.0.2
Streamlit component that allows you to have custom tabs with customizable styles
Requires Python: >=3.8

# streamlit_custom_tabs Component

Streamlit component that allows you to do X

## Installation instructions

```sh
pip install streamlit_custom_tabs
```

## Usage instructions

```python
import streamlit as st

from streamlit_custom_tabs import Tab_Bar


component1=  Tab_Bar(tabs=["Tab1","Tab2"],default=0,color="grey",activeColor="purple",fontSize="20px",key='bar')

#Handle your tabbar usecases here.
if(component1 == 0):
    st.write("Hooray! we are in Tab1")
else:
    st.write("Yippee! We are in Tab2 ")
```