Interleaving in Human learning

What is interleaving?

Interleaving is a learning technique that involves mixing together different topics or forms of practice, in order to facilitate learning

Imaging you are in a study session preparing for a test, a test that the would be comprised of various topics. How should you study for them? One at a time or switching between them?

Research suggest that you shouldn’t study one idea, topic or type of problem for too long. Instead you should switch it up often. Interleaving like this might seem harder than sticking to one topic or material for a long time, but it…


This Blog is a Walk through of my Cousera IBM Data scientist certification capstone project.

Disclamer:

This project was done in the middle of a pandemic so some of the data my be a little outdated and it may not be the best time to start a business. That been said, here is the report

Table of contents

Introduction:

  • Business Problem
  • Data
  • Methodology
  • Analysis
  • Results and Discussion
  • Conclusion

Introduction

In this project we will explore data from the city of New York. NYC need no introduction, it is one of the most populous city in United States with a population of…


Image Credits: hobbit (opens in a new window)/ Shutterstock

In my prior write-up, What’s your “Next-Flick”? An Introduction To Recommendation Systems, I tell the story of Netflix’s data-centric solution to tv programming that change the game till this day, with regards to how big data has become the major determinant of the decisions in the movie/Tv production and distribution industry as we know it today. For a company like Netflix , deciding what movie/ tv show to invest is one part of the problem big data provides solutions for, another even more important part is its distribution. With about 200million subscribers, with a constantly growing library , currently about…


How do you decide what movie/tv show to watch next? Most people find out about new movies from friends, people who are likely to be similar to themselves. While data science can’t make people friends (yet) it can attempt to mimic certain aspects of friendship when it comes to discovering new movies.That’s a scenario where the idea of recommendation systems can come into play.

Remember the TV show house of cards? Yea before Kevin Spacey…. Yea that show! The political drama that premiered on Netflix February 2013, it was Netflix’s first foray into original programming. It was a huge success…


What is the beautiful game? It translates from ‘O Jogo Bonito’ , a Portuguese phrase, made famous by Pele, a Brazilian footballer, that has been iconized in history because of the game of soccer.

As a big soccer fan, I know the right terminology is football in the rest of the world except North America, for the sake of clarity, I chose to call it soccer in the write up, I hope can find it in your hearts to forgive me and not get caught up in semantics.

Now that is out of the way, I’ve been an avid soccer…


In my previous article, Data Scientists, What Are Those?, I talked about the essence of a data scientist, there I pointed out four subject areas that a DS is expected to be somewhat skilled at, I called them “The four pillars of expertise”; business domain, computer science (programming), mathematics and communication . It’s important for a data scientist to piece together a compelling narrative, hence, I’ll be developing on one of these pillars, mathematics, specifically, statistics and some of the techniques implored by data scientist.


https://www.itworldcanada.com/blog/landing-that-dream-data-scientist-position/427272

Inspired by my last article, Graph databases, what are those? I decided to carry on in the same spirit of questioning and exploration. Taking a step back to the very beginning, I’ll be attempting to dissect the very concept of what it means to data-science, and try to paint a picture from my perspective. Moreover, I hope for this to serve as a reference to everyone that ever asks what I do.

It has been a couple of months into my journey as a Data scientist, I’ve completed the flatiron immersive Data science bootcamp, spent countless hours on stack overflow


The only constant is change. As a data scientist, this fact is ever so present in the world of artificial intelligence. New technologies are always emerging and can either be a catalyst to more efficient solution (if they are the right fit) or an unnecessary source of headache.

You might have heard of graph database technology and wonder what or why, or even concluded that it was just another trend. Well I’m going to tell all the basics you need to know and let you decide.

What is Graph Database (GDB)?

GDB is a method of storing , accessing and navigating related datasets using the…


Till this day, my favorite definition of a Machine is ; something that makes work easier. At its simplest, a machine is an invention that does a job better and faster and more powerfully than a human being. With regards to machine learning, this is the why. There is a need to preform a task more efficiently and at a faster rate. What is the task? to make decisions. Hence what then is Machine learning??

Before I answer that, a quick introduction. In my journey to becoming a data scientist, I found myself having to learn a lot of new…


René Descartes on his desk. Source: Wikimedia

I would like to take this opportunity accentuate what I consider one of the most important milestone / inventions in mathematics as a whole and the man that made this possible. Rene Descartes (1596–1650) is a French philosopher, mathematician and scientist responsible for the unification of algebra with Geometry , in the appendix of the Discourse on the Method, which giving rise to the emergence of analytic or Cartesian geometry (from Cartesius, the name Descartes in Latin). He was able to for the first time make a connection with algebra and geometry at a time when they were seen as…

Chibuzo Ugonabo

Data Scientist

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