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ab-testing-ad-campaign-performance-r

An advertising company is running an online ad for a client with the intention of increasing brand awareness. The advertiser company earns money by charging the client based on user engagements with the ad it designed and serves via different platforms. To increase its market competitiveness, the advertising company provides a further service that quantifies the increase in brand awareness as a result of the ads it shows to online users. The main objective of this project is to test if the ads that the advertising company runs resulted in a significant lift in brand awareness.

absenteeism_to_work_prediction

Employees can be absent to work due to many reasons. In this data science project, I used machine learning algorithm on an available dataset to predict if the employee will be absent to to some illness categories and other features.

advance-sql

Contained course material about advance MySQL function.

ai-programming-with-python-nanodegree

This repo contains notebooks and related code for Udacity's Deep Learning with PyTorch lesson. This lesson appears in our AI Programming with Python Nanodegree program.

audio_purchase_prediction_using_deep_learning

The main idea is that if a customer has a low probability of coming back, there is no reason to spend any money on advertizing to him/her. If we can focus our efforts ONLY on customers that are likely to convert again, we can make great savings. Moreover, this model can identify the most important metrics for a customer to come back again. Identifying new customers creates value and growth opportunities. You have a .csv summarizing the data. There are several variables: Customer ID, Book length in mins_avg (average of all purchases), Book length in minutes_sum (sum of all purchases), Price Paid_avg (average of all purchases), Price paid_sum (sum of all purchases), Review (a Boolean variable), Review (out of 10), Total minutes listened, Completion (from 0 to 1), Support requests (number), and Last visited minus purchase date (in days). So these are the inputs (excluding customer ID, as it is completely arbitrary. It's more like a name, than a number). The targets are a Boolean variable (so 0, or 1). We are taking a period of 2 years in our inputs, and the next 6 months as targets. So, in fact, we are predicting if: based on the last 2 years of activity and engagement, a customer will convert in the next 6 months. 6 months sounds like a reasonable time. If they don't convert after 6 months, chances are they've gone to a competitor or didn't like the Audiobook way of digesting information. The task is simple: create a machine learning algorithm, which is able to predict if a customer will buy again.

aws-slides

Contains screenshots of all the slides of Andrew Brown's AWS Course

aws-streaming-app

A Scalable #aws streaming Application for real time reporting.

c-_datastructure

Data structure in C++ repos

caption-project-unsupervised-anomalies-detection-in-iot-iiot-devices-fl

This repository contains the code for the the caption project submitted to be able to graduate in masters of computing.

causal-inference-logistic-optimization

Work on clients’ data to help it understand the primary causes of unfulfilled requests as well as come up with solutions that recommend drivers locations that increase the fraction of complete orders.

causal_inference

Work on clients’ data to help it understand the primary causes of unfulfilled requests as well as come up with solutions that recommend drivers locations that increase the fraction of complete orders.

connecting_python_and_sql

creative_optimization

Computer Vision for Creative Optimisation: KPI maximisation through image analysis

data-engineer-end-to-end-project-airflow-dbt-soda-bigquery

An end to end data engineering project for loading data into bigquery with airflow, perform transformations using dbt and do data quality check with soday

data-engineering-etl-ibm

extract transform and load and transfrom

data-engineering-zoomcamp

This repo contains homework and notes for the Data Engineering Zoomcamp by Datatalks.Club. Notes for the course. Final project

data-engineering_text-to-speech_data-collection-1

Data Engineering: text-to-speech data collection with Kafka, Airflow, and Spark

data-structures-algorithms-python.

This repository contains most needed data structures and algorithms needed to get start as python dev

data-warehouse--postgres-dbt-airflow

A city traffic department wants to collect traffic data using swarm UAVs (drones) from a number of locations in the city and use the data collected for improving traffic flow in the city and for a number of other undisclosed projects. Your startup is responsible for creating a scalable data warehouse that will host the vehicle trajectory data extracted by analysing footage taken by swarm drones and static roadside cameras. The data warehouse should take into account future needs, organise data such that a number of downstream projects query the data efficiently. You should use the Extract Load Transform (ELT) framework using DBT. Unlike the Extract, Transform, Load (ETL), the ELT framework helps analytic engineers in the city traffic department setup transformation workflows on a need basis.

datacamp-projects

datawarehouse-aws_s3-airflow-dbt

use the Extract Load Transform (ELT) framework using DBT. Unlike the Extract, Transform, Load (ETL), the ELT framework helps analytic engineers in the city traffic department setup transformation workflows on a need basis.

dbt-datacamp-course-note

dbt course form datacamp for data analytic engineer

detecting_covid-19_with_chest-x-ray

Detecting COVID-19 with Chest X Ray using PyTorch

eda_telecom_industry

Telecommunication Industry exploratory ana,ysis

elt_pipeline_project_2

Postgress based warehouse and superset based visualizer

ibm-data-engineering

in-context-learning-llms

The world is going through a revolution in art (DALL-E, MidJourney, Imagine, etc.), science (AlphaFold), medicine, and other key areas, and this approach is playing a role in this revolution. .

javascript-practice

This repository contains code to create a meet up app, twitter clone app, and many more apps. I used React 18, Javascript, HTML CSS.

machine-learning-process-a-z

The end-to-end process of building a Machine Learning Model.

mnist-federated

Experiments on MNIST dataset and federated training using Flower framework