pruthvirajpardeshi Goto Github PK

become-python-topgun

This repository contains a collection of 100 short Python programs that are perfect for beginners to use to learn and practice their Python programming skills.

canada-per-capital-income-prediction

I have studied a dataset of Canada's per capita income where I went through data analysis, data cleaning, and identification of key insights. Using a simple linear regression model through which we are  able to predict the future capital value using data cleaning, data visualisation, data mining, linear regression, and machine learning concepts.

customer-segment-analysis

There are many models for **clustering** out there. Despite its simplicity, the **K-means** is vastly used for clustering in many data science applications, it is especially useful if you need to quickly discover insights from **unlabeled data**. In this notebook, you will learn how to use k-Means for customer segmentation.

data-cleaning-.

Several data cleaning techniques, including catagorical missing value imputation, eliminating rows and columns, missing value imputation by mean, median, and mode, and lastly missing value imputation using Scikit Learn, have been used in this notebook .

datasets

drugs-recommendation-using-reviews

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

employee-salary-prediction-using-multiple-linear-regression

Using crucial data insights from analyses of the employee's experience, skill sets, and capacity to handle real-world problems, we constructed a model in this project to forecast the employee salary. Our model was then able to evaluate the employee's wage appropriately using regression analysis.

fraud-detection-in-online-transactions

Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting

ipl-data-analysis-

Used the IPL dataset to analyze player performance. Data visualization was done utilizing a variety of plots to get insights into the data, such as what factors affect player performance, the best IPL players, the biggest IPL matches, and the impact of the toss decision on a game

mobile-network-data-analysis

Applied stastical tests on mobile network dataset

old-car-value-prediction-

With the aid of critical data insights, such as our research of the production year, price, and how many years it has been in use, we were able to construct a model utilising  logistic regression methode to forecast the price of used automobiles for this project.

time-series-analysis

Stock price prediction by using time series analysis.In this project ARIMA model is used as dataset has treand and Saesonality both.As time series was not stationary initially we need to make it first stationary and then apply model and thus log transformation and differentiation ahs done on continueous data.

twitter-sentiment-analysis

It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization