Mehmet Tahir Aslan (mtahiraslan)

mtahiraslan

Geek Repo

Company:BeeBI Consulting GmbH

Location:Istanbul,Turkey

Twitter:@mhmthraslan

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Mehmet Tahir Aslan's repositories

data-analyst-roadmap

Based on my own experience, I think this roadmap will answer all the questions of how to become a data analyst from zero, which technologies and programming languages are better to know, what kind of soft skills do we need, how do I start my professional career in this field.

License:MITStargazers:308Issues:6Issues:0

rule_based_classification

It is an application that estimates how much a new customer can earn on average and in which segment by applying EDA (Exploratory Data Analysis), segmentation and forecasting methods on persona.csv (customer dataset) using the Streamlit library.

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8_week_sql_challenge

SQL solutions for #8WeekSQLChallenge questions by Danny Ma

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flo_cltv_prediction

FLO wants to determine roadmap for sales and marketing activities. In order for the company to make a medium long -term plan, it is necessary to estimate the potential value that existing customers will provide to the company in the future.

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python-api-with-docker-and-postgres

This project integrates real-time cryptocurrency data into a PostgreSQL database using Docker, PostgreSQL, pgAdmin, Python, and CoincapAPI. It streamlines the process of fetching, transforming, and storing market data, offering a portable and easily set-up solution for data analysts and crypto enthusiasts.

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ab_testing_project

Comparison of A/B Test and Conversion of Bidding Methods

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flo_rfm_analysis

FLO, which is an online shoe store, wants to divide its customers into segments and determine marketing strategies according to these segments. For this, the behavior of customers will be defined and groups will be formed according to the clutches in these behaviors.

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rating_products_sorting_reviews_amazon

Rating Product & Sorting Reviews in Amazon

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armut_arl_recommender_system

An association rule learning-based product recommendation system is desired to be created using the dataset containing users who received services and the categories of services they received.

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