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1

Diabetes-Prediction-App

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2

Stocks-Price-EDA-Time-Series-Project-

## Tasks: 1) Analyze closing price of all the stocks. 2) Analyze the total volume of stocks being traded each day. 3) Analyze daily price change in stock. 4) Analyze monthly mean of close feature. 5) Analyze whether Stock prices of these tech companies are correlated or not. 6) Analyze Daily return of each stock and how they are co-related. 7) Value at risk analysis for Tech Companies.
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3

Airline-Price-Prediction-with-Deployment-

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4

Feature-Engineering---Real-World-Dataset

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5

Zomato-Restaurant-Rating-Prediction

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6

Zomato-Spatial-Analysis

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7

Data-Cleaning---Movie-Dataset

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8

Car-Price-Prediction

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9

YouTube-Text-Analysis

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10

Exploratory-Data-Analysis---Terrorism

● Perform ‘Exploratory Data Analysis’ on dataset ‘Global Terrorism’ using Tableau ● As a security/defense analyst, try to find out the hot zone of terrorism. ● What all security issues and insights you can derive by EDA?
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11

DogeCoin-Price-Prediction

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12

Loan-Status-Prediction

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13

Bank-Note-Authenticator

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14

Prediction-using-Supervised-ML

Predict the percentage of an student based on the no. of study hours.
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15

Car-Selling-Price-Prediction

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16

Data-Visualization

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17

Chronic-Kidney-Disease-Prediction

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18

Imputing-missing-Values-in-FIFA-Dataset

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19

Data-Processing

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20

Bike-Rental-Demand-Prediction

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21

Data-Cleaning---Naukri-Dataset

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22

Computer-Price-Prediction

Task is to create a machine learning model which can predict the price of a computer based on its specs.
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23

PyCaret

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24

Finding-and-Handling-Outliers

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25

Feature-Engineering-

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26

Diamond-Price-Prediction

Business Scenario: A diamond merchant has come to you for help. They want to create an automated system to predict the apt price of a diamond based on its shape/size/color etc.
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27

Data-Cleaning---BigMart-Dataset

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28

Prediction-using-Unsupervised-ML-K-Means-Clustering-

From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
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29

Exploratory-Data-Analysis---Sports

● Perform ‘Exploratory Data Analysis’ on dataset ‘Indian Premier League’ ● As a sports analysts, find out the most successful teams, players and factors contributing win or loss of a team. ● Suggest teams or players a company should endorse for its products.
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