Machine Learning - lesson 7 | HackIndia Skills

Machine Learning - lesson 7 | HackIndia Skills | HackIndia

Example

README starter

Use this as a plain starting point. Replace the example text with your project details.

If you use AI to draft the README, check every command, file name, metric value, and dataset link before committing it.

# Student Placement Predictor

## Problem
Predict whether a student gets placed using tabular student data.

## Dataset
Source: <paste dataset link or official source here>
Target column: placed
Rows used: <number>

## Train/test split
Split: 80% train, 20% test
Random state: 42
Test data was not used for training.

## Model
scikit-learn LogisticRegression
Reason: simple baseline for a binary classification problem.

## Result
Metric: accuracy
Test accuracy: 0.82

## How to run
1. Clone this repo
2. Install dependencies:
   pip install -r requirements.txt
3. Train and evaluate:
   python train.py

Example

Small train file

This is enough for a starter repo if your CSV is already cleaned. Keep names readable.

Do not copy this blindly. Change the file name, target column, model, and metric for your own project.

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score

DATA_PATH = "data.csv"
TARGET = "placed"

 df = pd.read_csv(DATA_PATH)
X = df.drop(columns=[TARGET])
y = df[TARGET]

X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42
)

model = LogisticRegression(max_iter=1000)
model.fit(X_train, y_train)

preds = model.predict(X_test)
score = accuracy_score(y_test, preds)

print(f"Test accuracy: {score:.3f}")

Ship the ML repo

Proof beats claims

What your repo needs

Use this structure

README starter

Small train file

Do not hide data

Commit like a builder

Do this now

Quick check