Ppt describing heart disease prediction, dataset, and models.

1. Heart Disease
Prediction
By-
Rajkumar Ramteke B520043 (search strategy)
Punit B520040 (data collection)
Akankhya Mishra B520004 (evaluation)

2. Cardiovascular Disease (CVD),
commonly referred to as heart
disease, encompasses a wide
range of conditions that affect the
heart, with the two most common
conditions being ischemic heart
diseases and strokes.
Data Acquisition
evaluating physical conditions and considering the numeric data
Data Pre-processing
Checking for missing values and outliers.
Data Integration
evaluating physical conditions and considering the numeric data
Data Analysis
evaluating physical conditions and considering the numeric data
Data intervention
to get into the decision-making policies

3. Exploration of Dataset
Age Sex cp Trest
bps
chol fbs restec
g
thalac
h
exang Old
peak
63 1 3 145 233 1 0 150 0 2.3
37 1 2 130 250 0 1 187 0 3.5
41 0 1 120 204 0 0 172 0 1.4
57 0 1 140 236 0 1 178 1 0.8
slope ca thal
0 0 1
0 0 2
2 0 2
2 0 2

4. 4 Presentation title 20XX
Raw
data
Data
Preprocessi
ng
Processed
data
Train
Model:
Validation
on accuracy
Test
Accuracy
Satisfies
Accuracy?
Deploy
Model
Simulation job
From advanced
nodes
ML Model &
Tuning
n
o
yes

5. ML Models
Logistic
regression
Support
Vector
Machine
Random
Forest
Naïve
Bayes XG Boost
5 Presentation title 20XX