kumarg160491 Goto Github PK

-health-care-index-2020-analysis

amexpert_analytics-vidya

arima--daily-total-female-births-california-1959

arima-of-14-mins-stock-prediction-from-kaggle

breast-cancer-prediction-using-pca

capston-project-webscraping--data-extraction-and-text-analysis

cat-dog_detection

credit-risk-analysis--loan-lendingclub

customer-churn-prediction_pipeline

data-analysis

Directory is having dataset and file related to Data Analysis

data-science-and-business-analytics-internship---the-spark-foundation

This Folder is created for Data Science and Business Analytics Internship - The Spark Foundation

decodr-folder

divorce-predictors-data-set

feature-engineering

genai_geminipro_streamlit

git_test

just for test

hackathon--dream-housing-loan-prediction

heroku-model-deployment

hr_candidate_hiring_prediction_analysis

Machine Learning and Deep Learning Projects

identify-the-sentiments-of-tweeter

installation-of-anaconda-on-linux-ubuntu

internship_task_socialmedia.com

janatahack----hr-analytics

janatahack--nlp-hackathon

JanataHack- NLP Hackathon

janatahack--time-series-forecasting

Company of Electrolysia supplies electricity to the city. It is looking to optimise its electricity production based on the historical electricity consumption of the people of Electrovania. The company has hired you as a Data Scientist to investigate the past consumption and the weather information to come up with a model that catches the trend as accurately as possible. You have to bear in mind that there are many factors that affect electricity consumption and not all can be measured. Electrolysia has provided you this data on hourly data spanning five years. For this competition, the training set is comprised of the first 23 days of each month and the test set is the 24th to the end of the month, where the public leaderboard is based on the first two days of test, whereas the private leaderboard considers the rest of the days. Your task is to predict the electricity consumption on hourly basis. Note that you cannot use future information to model past consumption. For example, you cannot use February 2017 data to predict last week of January 2017 information.

janatahack-machine-learning-for-banking

janatahack-mobility-analytics

k-mean-clustering

kaggle-airbnb

kmean-clustering-using-r