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Data Science and Business Analytics Task-1 (Predict the percentage of an student based on the no. of study hours)
Data Science and Business Analytics Task-1 (Predict the percentage of an student based on the no. of study hours).
This Repository is dedicated to the completion of my Task with video from The Sparks Foundation (Graduate Rotational Internship Program).
Basic Banking System
Create a hybrid model for stock price/performance prediction using numerical analysis of historical stock prices, and sentimental analysis of news headlines, Stock to analyze and predict - SENSEX (S&P BSE SENSEX) Download historical stock prices from finance.yahoo.com Download textual (news) data from https://bit.ly/36fFPI6 Use either R or Python, or both for separate analysis and then combine the findings to create a hybrid model You are free to select a different stock to analyze and news dataset as well while not changing the objective of the task.
Task-1 (Predict the percentage score of an student based on the no. of study hours)
It contains the task assigned me for my internship, the task was very simple, I just had to predict the marks of students using Machine Learning, it was very easy.
The Sparks Foundation Internship for Data Science/Analytics.
Internship projects of The Sparks Foundation
A basic banking system which will just transfer money between multiple customers.
‘Exploratory Data Analysis’ on dataset ‘Indian Premier League’ . 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.
GRIP the spark foundation task 5 - Social media integration
This is an internship task of web development intern under GRIP MAY 2021 of The Sparks Foundation Company.
Implement a real time face mask detector. ● Below resources are just for references you can use any library/approach to achieve the goal. ● Resources: link1 link2 ● Task submission: 1. Host the code on GitHub Repository (public). Record the code and output in a video. Post the video on YouTube 2. Share links of code (GitHub) and video (YouTube) as a post on YOUR LinkedIn profile 3. Submit the LinkedIn link in Task Submission Form when shared with you. 4. Please read FAQs on how to submit the tasks.
Implement a Fault Detection System which, detects and eliminates the faulty products based on the shape/colour. ● Please go through the below link for more understanding ● Resources: link1 ● Task submission: 1. Host the code on GitHub Repository (public). Record the code and output in a video. Post the video on YouTube 2. Share links of code (GitHub) and video (YouTube) as a post on YOUR LinkedIn profile 3. Submit the LinkedIn link in Task Submission Form when shared with you. 4. Please read FAQs on how to submit the tasks.
Create a storyboard showing spread of Covid-19 cases in your country or any region (Asia, Europe, BRICS etc) using Tableau, Power BI or SAP, Use animation, timeline and annotations to create attractive and interactive dashboards and story Identify interesting patterns and possible reasons helping Covid-19 spread with basic as well as advanced charts Screen-record the completed storyboard along with your audio explaining the charts and giving recommendations. Dataset: Daily updated .csv file on https://bit.ly/30d2gdi
Task 01: Predict the percentage of an student based on no of study hours with Supervised Machine Learning
Task 02: Clustering using Unsupervised Machine Learning
This repository contains all the task which I have performed under "The Sparks Foundation" as a data science & business analytics Intern. 📝
GRIP - Graduate Rotational Internship Program
Tasks Assigned to me for this WFH internship via TheSparksFoundation.
The Spark Foundation Internship in the domain of Data Science & Business Analytics
These are the tasks provided by The Sparks Foundation for the #GRIPNOV20 for Data Analysis internship.
This app is developed to complete Task #5 of the Graduate Rotational Internship Program (GRIP) by The Sparks Foundation.
The Sparks Foundation Internship Project - Payment Gateway Integration #Task2
Task: Prediction using Supervised ML - Predicting the percentage of a student based on the no. of hours studied using a simple linear regression model. Dataset available at http://bit.ly/w-data. Tools used: Python, Jupyter Notebook
GRIP@ | Sparks Foundation | web development internship | Task-1 | Basic Banking system
This is a repository for my internship task at TSF.
This app was developed to complete Task #2 of the Graduate Rotational Internship Program (GRIP) by The Sparks Foundation.
IPL ANALYSIS 2002-2022 Dashboard
GRIP - Graduate Rotational Internship Program
GRIP - Graduate Rotational Internship Program