(Big)Data Science & Engineering

Wer schon einmal versucht hat, in Wien eine Eigentumswohnung zu finden, kennt das Problem: willhaben hat tausende Inserate, die Filter sind ungenau, und am Ende sitzt man mit 20 offenen Browser-Tabs da — ohne echten Überblick über den Markt. Genau so ging es mir. Ich denke gerade ernsthaft darüber nach, in Wien eine Wohnung zu kaufen. Und dabei bin ich auf ein Tool gestoßen, das meine Suche…

Coronavirus (COVID-19) outbreak brought the world economy and the stock market to their knees. Many people and most companies are fighting to survive these hard times. On the other hand, some are using this situation to make huge profits. In this experiment I demonstrated how to make over 80% gains, while the whole stock market is crashing, in less then a month by trading US equities. Similar,…

Graph Data Structure – Python Implementation

Today, as the data volumes are growing almost exponentially, search in artificial intelligence and computer science is regaining it’s popularity. There is basically no field without application of at least some of the search algorithms. Many of the search algorithms in computer science and artificial intelligence rely heavily on graphs and trees as underlying data structure for performing search…

The Universe of Stocks – Quant Finance Visualization

I always asked myself how to visualize stock performance by sector properly. It is a fact that Visualization is underrated in the field of Quantitative Finance. So here is my contribution to the Visualization Techniques for Quantitative Finance.

Finance research by Dženan Hamzić

Finance research by Dženan Hamzić

Finance research by Dženan Hamzić

Finance research by Dženan Hamzić

Finance research…

Artificial Neuron learning in Python

It all starts with a single neuron! Or with a perceptron. Perceptron is a neuron’s computational model. If you link some of them together, you get to a real ‘artificial brain’ capable of learning complex stuff.

When I try to explain basic AI concepts to non computer scientist, I start like this… You have a baby that knows nothing. At the beginning, the baby makes many mistakes, but improves over…

https://plot.ly/~dzhamzic/39.embed

https://plot.ly/~dzhamzic/33.embed

Vizuelna Analiza Trzista Nekretnina Bosne i Hercegovine

Gdje kupiti, iznajmiti ili prodati nekretnine u Bosni i Hercegovini. Ova vizuelna prezentacija ce vam pomoci oko nekih bitnih pitanja. Izvolite…

Analiza nekretnina u Bosni i Hercegovini – Dzenan Hamzic

  Analiza nekretnina u Bosni i Hercegovini – Dzenan Hamzic

Boston Consulting Group Matrix Visualisation

Recently, I had to make a Boston Consulting Group Matrix for a Strategic Management Class. I started off by doing everything in Python (Product-line growths etc.) and wanted to make a nice plot, but, plotting BCG Matrix in python is a bit overhead and I switched to  QlikView eventually, which I wanted to try out for a long time anyway.

Nuff’ sad, here is the BCG Matrix in QlickView:

Not sure about the game outcome? Simulate the game!

“Suppose you’re on a game show, and you’re given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the doors, opens another door, say No. 3, which has a goat. He then says to you, “Do you want to pick door No. 2?” Is it to your advantage to switch your choice?” source: Wikipedia

Would you stick to your…

3D Interactive Hotel Market Segmentation

There is a life beyond regression analysis! You can do so much more with pure time-series data!

Some while ago I asked myself what could be learned about Viennese 3 star hotels from a bunch of time-series data. I applied some machine learning techniques, including multidimensional scaling and k-means clustering with “almost” ad hoc knee point, and finally visualized results with plotly in 3D.  If…

Web Mining on CSS classes

I was just working on some ‘side projects’ and made some nice visualizations of CSS classes as graph structures from Amazon, The New York Times and some other sites. Some interesting clusters can be spotted. Somehow, I have a feeling, I’m gonna dig deeper into this things of WebMining…

Check out the plots below. Cheers!

Klix.ba CSS graph

The New York Times CSS graph

Klix.ba CSS graph

The New York…

Market Basket Analysis in Python #python #datascience #association #mining

Have you ever asked yourself how the store managers decide on product shelf placement in retail stores? There must be some strategy behind it, right? It can’t be just a random choice. Almost on daily basis, you receive product purchase recommendations from variety of sources where you have left your “digital fingerprint”. In many cases these recommendations make sense, what leaves you puzzled,…

Bloom Filter in Python #datascience #datamining #python

The title might also have been, “how to reduce 10 Gb of data to 1 single Megabyte”. BigData is only going to get bigger in the future. Our challenge, among others, is to find efficient methods and algorithms to (quickly) deal with  wast amounts of data, extract meaningful information and to find ways how to efficiently persist all these data.

That is where the Bloom filter comes in…

The Bloom…

Recommender System in Python #python #datascience #recommendersystem

The Amazon and Netflix are making almost 50% of their revenues by recommending appropriate products (books, movies) to their users. But how do they know what to recommend to their users? Well, they use the power of the collaboration between all other items and users.

Collaborative Filtering(CF) is maybe the most popular method in Recommender Systems at the moment. For predicting the unknown…

As the end of year 2016 is approaching, I decided to gather and summarize my visualizations on one page. Have a look.

Happy new year! Cheers!

#visual #analytics #bigdata #BI #ML #datamining #mmds #plots 

Post by @dzhamzic.

Source: Visual Gallery

From Recursion to Tail Recursion in Scala #scala #recursion #optimization

Tail recursion is a kind of special recursion where the last call in function, calls another function or itself. It is basically a functional form of a loop and is advantageous while the function does not have to wait for the result of inner functions and does not fill the memory stack. The tail recursion has a fixed stack size and does not lead to a stack overflow. Since most JVM implementations…