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import streamlit as st
import numpy as np
import pandas as pd
st.header(":red[**Life Cycle Of Machine Learning Project**]")
st.write(":blue[Click the button below to explore detailed steps involved in an ML project:]")
if st.button("**Problem Statement**"):
if st.link_button("**Problem statement of Machine Learning**"):
st.write("""
*A problem statement in machine learning defines the specific issue you want to solve using data and machine learning techniques. It should clearly explain:**
- What the problem is
- Why solving it is important
- What data is available
- What the expected outcome will look like
""")
st.write("""
**Examples of ML Problem Statements:**
- **Predicting House Prices:**
- Problem: We want to predict the price of houses based on features like size, location, number of bedrooms, etc.
- Why: This helps buyers make informed decisions and real estate agents price houses correctly.
- Data: Historical data about house prices and their features.
- Expected Outcome: A model that predicts the price of a house given its features.
""")
if st.button("**Data Collection**"):
if st.link_button("**About Data Collection of Machine Learning**"):
st.write("")
#if st.button("**Simple EDA**"):
#if st.button("**Data Pre-processing**"):
#if st.button("**Exploratory Data Analysis (EDA)**"):
#if st.button("**Feature Engineering**"):
#if st.button("**Training**"):
#if st.button("**Testing**"):
#if st.button("**Deployment**"):
#if st.button("**Monitoring**"):
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