A 22 years old IT engineer student. https://github.com/ahmedazizkhelifi

Not only Jupyter. Google Colab, R Markdown, and much more.

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Interactive notebooks are experiencing a rise in popularity. Why?
Simply because it’s a great teaching environment, powerful, shareable, and provides the ability to perform data visualization in the same environment. Which interactive notebooks should I use? I recommend:

Machine Learning Problems

Top 6 Machine Learning Solutions to Business Problems

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Introduction

Data science and machine learning are two very popular words when talking about the Big Data revolution, behavior prediction, or simply the digital transformation of companies.

They are new fields of work, which have augments traditional analytical capabilities to help companies make better decisions. …

VPython

Simulate complex physics equations

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Introduction

Physical science is based on simplifications and approximations: orbits are always circular, projectiles fly without air resistance, pendulums swing only at small angles. These kinds of simplifications are necessary and appropriate when you’re first trying to understand the basic laws of nature, (those approximations are useful, we lose a little…

SQL | PYTHON | RELATIONAL ALGEBRA

Understand SQL, Relational Algebra, Relational Databases, and SQlite3 for Python

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Plan

  1. Basic concepts and terminology.
  2. Creation of a relational schema with SQL (DDL).
  3. Relational algebra.
  4. Aggregation functions.
  5. DML (Data Manipulation Language).
  6. DQL (Data Query Language) (SELECT query).
  7. Access to databases with Python (sqlite3 module).

Basic Concepts and Terminology

DATA ANALYSIS

Descriptive statistics is crucial before the process of inferential

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Table of contents

  1. Introduction
  2. Data types
  3. Analyzing Quantitative Data
    I.
    Measures of Center
    II.
    Measures of Spread
    III.
    Shape of distribution
    IV. Outliers
  4. Descriptive vs. Inferential Statistics
  5. Looking Ahead
  6. Summary

Introduction

The word “data” is defined as distinct pieces of information. You may think of data as simply numbers on a spreadsheet, but it…

DATA SCIENCE

With examples from the world of Data Science

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Table of contents

  • What’s Recursion?
  • Recursion in Programmation
  • Examples from the worlds of Data Science
  • Conclusion

What’s Recursion?

Recursion is a concept that refers to itself in its operation. This is found in all artistic fields: literature (mise en abyme), painting, photography …
A physical world example would be to place two parallel mirrors facing each…

Wirecard collapse and EY at the heart of the affair

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Since Friday 25 July 2020, all operations were prohibited after the bankruptcy of the German giant of online payments Wirecard.

Wirecard, a company with multiple activities

There are two major countries for Wirecard. First, in the United Kingdom where we can find the company “Wirecard Card Solutions Ltd (WDCS)” but also “Wirecard Bank AG”. …

Image source: Github Satellite

All you need to know about the GitHub Satellite 2020

What’s GitHub?

Github is a platform that helps developers around the world to work and collaborate with each other, it’s also the biggest source of open-source projects…

Check this video for more information

What‘s GitHub Satellite?

GitHub Satellite is an annual international event — actually, it’s the largest developer event outside the US, that brings…

Data Science

Understand Data Science and Data Types (Structured, Unstructured …)

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Table of contents

  1. What’s Data Science?
  2. Is Data Science a New Filed?
  3. Types of Data
  4. Data Formats/Sources
  5. Summary and Conclusion

What’s Data Science?

Data science is the study of large quantities of data. Like biological sciences is a study of biology, physical sciences, it’s the study of physical reactions. It is the process of using data…

Khelifi Ahmed Aziz

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