Adeela12

PRECON_DATASET

PRECON is a first of its kind extensive dataset of electricity consumption patterns of users in developing countries. The dataset has been collected through smart meters over a period of one year and comprise of data of users belonging to different demographics and different social and financial backgrounds. It provides details of electricity consumption data and meta-data of houses opted for data collection. Also, we have provided details on high electricity consumption devices and the load profile of the whole house. The aim of this data collection and processing exercise is to understand the electricity consumption patterns of users in the developing world. A sound realization of consumption patterns can help in the development of intelligent smart grids and better demand-side management tools. PRECON is unique from the datasets of its kind because it is only extensive dataset collected over a period of one year which is publically available. Other than that it is different in terms that it monitors a greater number of households than any other similar dataset of developing countries.

Data-collection-and-processing-with-Python-week1

Data-Collection-and-Processing-with-Python-Week2

Data-Collection-and-Processing-with-Python-Week3

data_upload

first_streamlit_app

Kubeflow

Load-Forecasting

Machine-Learning-Projects

Machine_Learning

This repository contains all the projects related to Machine Learning.

Omniglot

Predicting_Click-Through

applying machine learning techniques to maximize the click-through for the presented choices.

RockPaperScissor-AI-

Building an AI to play Rock Paper Scissor using Neural Networks

Thesis

time-series-feature-extraction

Feature extraction examples using khiva and tsfresh libraries