arfanulaziz Goto Github PK

airline-customer-value-analysis-case-with-clustering-k-means

Segment airline customers, analyze the characteristics of different customer categories, compare the value of customers from different customer categories, provide personalized services for categories of customers with different values, and formulate the right marketing strategy.

arfanulaziz

Config files for my GitHub profile.

arfanulaziz.github.io

Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.

data-analyst-with-python

In this Datacamp learning track, you’ll learn how to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You’ll also gain experience of working with real-world datasets, including data from the Titanic and from Twitter’s streaming API, to grow your data manipulation and exploratory data analysis skills, before moving on to learn the SQL skills you'll need to query data from databases and join tables. Start this track, grow your Python and SQL skills, and begin your journey to becoming a confident data analyst.

datacamp-data-analyst-with-python

data analyst with python career track

exploratory-data-analysis-with-python

This is Hands on Exploratory Data Analysis with Python using Google Colabs This material provided by Rakamin Academy in Rakamin Trial Class

exploratory-data-with-python

goodboychan.github.io

jupyter blog

mock-request

Mock an API request and obtain a pre-saved response object

sql-analyze-international-debt-statistics

The dataset contains information about the amount of debt (in USD) owed by developing countries across several categories

use-nlp-and-clustering-on-movie-plot-summaries-from-imdb-and-wikipedia-to-quantify-movie-similarity.

Use NLP and clustering on movie plot summaries from IMDb and Wikipedia to quantify movie similarity