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abtest-mlops

Design a reliable hypothesis testing to test if the ads that the advertising company runs resulted in a significant lift in brand awareness. Used hypothesis A/B testing to test if a creative ad campaign resulted in a significant lift in brand awareness. Applied machine learning approach for A/B testing and compared its result with the hypothesis A/B testing result.

agritech-lidar-data-pkg

PythonLidar is an open-source python package for retrieving, transforming, and visualizing point cloud data obtained through an aerial LiDAR survey

agritechpkgdoc

amazon-sagemaker-ground-truth-task-uis

Example task UIs for Amazon SageMaker Ground Truth

amharic-to-esl-translator

amharic_model

set of language models for Amharic Language

c-header

casual-graph

Machine learning algorithms tend to focus on making the most accurate predictions or classifications rather than providing insights on the cause-and-effect relationships of features. But unlocking the cause and effect relationship can be important in decision making, especially in the sectors of health. It would also help to build more accurate models that exploits not only the data but also the cause and effect structure of the data. Casual inference is to infer what causes what. Casual inference enables us to answer questions like what causes what or what would be the effect if we improve some features ? This type questions can not be answered by machine learning algorithms only. we may calculate correlation or feature importance from machine leaning models, but machine learning algorithms captures association or correlation and not causation.

dictionary

dictionary1

discord_el

dos

dos3

facebooknotification

funcparser

git-get-started-b4

mini-dictionary

ministockapp

mystore2

newsbot

parser

pharmaceutical-sales-prediction

The finance team of Rossmann wants to forecast sales in all their stores across several cities six weeks ahead of time. Managers in individual stores rely on their years of experience as well as their personal judgement to forecast sales. The task was to build and serve an end-to-end product that delivers this prediction to analysts in the finance team.

pytorchtutorial

PyTorch Tutorials from my YouTube channel

rossman-sales-pred-dashboard

sample_app

sensor-data-elt

sensor_data_elt_dashboard

sharedmemoryandmessagepassing

sharedmemoryandmessagepassing2

smartad_abtest