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Name: Abdullah Elsayed
Type: User
Bio: I believe that Behind every great database, there's a great story. Be a Data scientist to discover that story, tell it, and sometimes predict it.
Location: Cairo, Egypt
Name: Abdullah Elsayed
Type: User
Bio: I believe that Behind every great database, there's a great story. Be a Data scientist to discover that story, tell it, and sometimes predict it.
Location: Cairo, Egypt
Practiced working with some of the difficulties for understanding and interpreting the results of the A/B test run by an e-commerce website.
Predict whether income exceeds $50K/yr based on census data
This project is all about clean and analyze data set for tmdb movies and extract useful information from it then communicate results
π Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A fictional telco company that provided home phone and Internet services to 7043 customers in California in Q3.
The main libraries for data visualization with Python and all the types of charts that can be done with them. We will also see which library is recommended to use on each occasion and the unique capabilities of each library.
It's will be a great Journey to Walkthrough this Project and discover a lot of information about Retail Business, Market, Target Customer, Geo, Brands, Sales and Forecasting
Start a data science project with modern tools
Create, update and delete from SQL Server using Flask
Connect to teradata or any DB using Pyodbc and teradatasql and Fetch your data to DataFrame using Pandas
For the case study, will concentrate only the variables in the top five bullet points: price and the four 'C's of diamond grade. Our focus will be on answering the question about the degree of importance that each of these quality measures has on the pricing of a diamond, and make prediction using linear regression algorithm
In this project, I will employ several supervised algorithms of my choice to accurately model individuals' income using data collected from the 1994 U.S. Census. I will then choose the best candidate algorithm from preliminary results and further optimize this algorithm to best model the data. my goal with this implementation is to construct a model that accurately predicts whether an individual makes more than $50,000. This sort of task can arise in a non-profit setting, where organizations survive on donations. Understanding an individual's income can help a non-profit better understand how large of a donation to request, or whether or not they should reach out to begin with. While it can be difficult to determine an individual's general income bracket directly from public sources, we can (as we will see) infer this value from other publically available features.
Dream Housing Finance company deals in all home loans. They have presence across all urban, semi urban and rural areas. Customer first apply for home loan after that company validates the customer eligibility for loan. Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customers segments, those are eligible for loan amount so that they can specifically target these customers.
Letβs see the main libraries for data visualization with Python and all the types of charts that can be done with them. We will also see which library is recommended to use on each occasion and the unique capabilities of each library.
Web scraping with Scrapy framework
EDA and Predict who will move to a new job
This project is a front end website for Lightup CO.
Prosper is a peer-to-peer lending platform that aims to connect people who need money with those people who have the money to invest. In this data analysis project, I have explored the Prosper dataset, prepare it for analysis and used 'Pyplot and Seaborn' to create my visualization and communicate results.
1. Geography Analysis and Visualization. 2. Product Analysis and Visualization. 3. Channels and Promotions Analysis and Visualization. 4. Customers (Persons) Analysis and Visualization.
Historical sales data for 45 stores located in different regions - each store contains a number of departments. The company also runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of which are the Super Bowl, Labor Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. πππ
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.