Natnael Masresha's repositories
Datawarehouse
Fully dockerized Data Warehouse (DWH) using Airflow, dbt, PostgreSQL and dashboard using redash
Prompt-engineering
A client has a system that collects news artifacts from web pages, tweets, facebook posts, etc. The client is interested in scoring a given new artifact against a topic. The client has hired experts to score a few of these news items in the range from 0 to 10; a score of 0 means the news item is totally NOT relevant while a score of 10 means the news item is very relevant. The range of results between 0 and 10 signifies the degree of relevance of the news item to the topic. The client wants to explore how useful existing LLMs such as GPT-3 are for this task. You are hired as a consultant to explore the efficiency of GPT3-like LLMs to this task. If your recommendation is positive, you must demonstrate that your strategies to design prompts are reproducible and produce a consistent result. You should also set up an MLOps pipeline that helps automate the task of using different LLMs and different topics. Your pipeline should also allow future improvements in the prompt design to be integrated without breaking the system. A centralized log system should be incorporated into your pipeline to help monitor outputs, cost, performance, and other relevant artifacts
Design-Patterns
A demonstration of how the design patterns work in C#. Here you can find the three design patterns: Factory Method, Abstract Factory, and Singlton. For more information about design patterns have a look at
Monty-Hall-Problem
The Monty Hall problem is a brain teaser, in the form of a probability puzzle, loosely based on the American television game show Let's Make a Deal and named after its original host, Monty Hall.
pharmaceutical-sales-prediction
The finance team in a pharmaceutical sales 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 judgment to forecast sales. The data team identified factors such as promotions, competition, school and state holidays, seasonality, and locality as necessary for predicting the sales across the various stores. This aim of this project is to build and serve an end-to-end product that delivers this prediction to analysts in the finance team.
.Netcore_postgres_CRUD_demo
A simple MVC CRUD web app using .NET Core and PostgreSQL
10AC-A_B-Hypothesis-Testing
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.
A_B-Hypothesis-Testing
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.
Causal-Inference
Logistic optimization: Delivery drivers location optimization with Causal Inference
computerVision
Computer Vision for Creative Optimisation: KPI maximisation through image analysis
Data-Engineering_text-to-speech_data-collection
Data Engineering: text-to-speech data collection with Kafka, Airflow, and Spark
Refund-by-Location-Smart-Contract
Web3: Refund by Location Smart Contract
Simple_CRUD_API
Very simple web API : with CRUD Functionality
Trading-Engineering_Scalable-Backtesting
Cryptocurrency trading engineering: A scalable back testing infrastructure and a reliable, large-scale trading data pipeline