Most investors are familiar with the NASDAQ composite index, a stock market index which is one of the three most-followed stock market indices in the United States and known to be high-tech and growth-oriented. However, you might not be familiar with the Hang Seng Tech index, Hong Kong’s new technology-focused stock index.
With the Asian tech sector rivaling the American one, lots of investors wanted to invest in it but were hesitant due to a lack of available ETFs, meaning they would have had to buy individual shares of each company, leading to excessively high fees.
Now, it is finally possible due to the creation of a new index: the Hang Seng Tech index. Launched on the 27th of July 2020, this new index is composed of 30 stocks listed in Hong Kong in the internet and information technology businesses and includes heavyweight Chinese tech giants such as Tencent, Alibaba and Meituan. …
In this tutorial, we will be using a dataset from the Machine Learning Repository of the University of California, which contains key financial indicators about companies.
We will use this data to predict if a company has filed for bankruptcy or not.
To make our predictions, we will use a logistic regression model, implemented using scikit-learn in Python.
For this tutorial, you need to have downloaded:
I’d also recommend using a Jupyter Notebook over an IDE.
The code and dataset are available on my GitHub.
I would suggest downloading a copy of the repository before getting started. …
Earlier this year, the big honcho across the channel, Emmanuel Macron, made a call to his people to “invest, work, and invent’’. France is trying to become a ‘start-up nation’, passing new laws that will hopefully see its unicorn (or licornes, as the French call them) count skyrocket.
A unicorn is a startup with an equity valuation of more than $1bn. Think of the likes of Uber, AirBnB, WeWork (ok, maybe not WeWork). These companies are usually relatively young, but fast growing.
Many of them are also characterised as loss making due to their break-neck levels of expansion. They use much of the investments made into them for the sake of widening their scope, with any money that they do make funnelled right back in. …
For developers designing a DBMS (Database Management System), one of the first questions that arises is: which type of databases should be used, SQL or NoSQL?
SQL or relational databases first came into play in the 1970s in a paper called “A Relational Model of Data for Large Shared Data Banks” published by Edgar Frank Codd, an IBM researcher (Codd, 1970).
On the other hand, NoSQL databases appeared twenty years later, in the 1990s, and were developed to meet the need for processing vast amounts of unstructured data that came with the big data era (Stonebraker, 2010).
At the moment, SQL is still the clear winner, even if NoSQL has gained ground since the last 20 years. …
People like to focus on the technology side of digital transformation. However, at its core, it’s more than technology: it is how organizations leverage the power of tech to improve customer experiences, increase operational efficiency and renew outdated business models (CDW, 2018).
The main goals of a digital transformation
According to Peter Sondergaard, a senior vice president at Gartner, a digital transformation has 4 key objectives: greater profitability of the organization, enhanced customer experience, better agility and improved competitiveness (Sondergaard, 2018). Thus, what digital initiatives can organizations take to reach those goals?
Digital transformation initiatives
According to a research from MIT Sloan, digital transformation initiatives can transform 3 things: customer experiences, operational processes or business models (Westerman, Bonnet and McAfee, 2014). …
For those of you doing Data Science projects, using .csv files is an essential part of the job, especially when working with pandas dataframe. However, the question is: where do you store this .csv file so that you can easily access it in the code?
To avoid any paths problems and have a file readable from any platform, a solution I recommend is to put the .csv file in a GitHub repository and access it directly in the code.
This allows you to have everything in the same place: the code and the data. Also, if you want to change your dataset, all you need to do is update the .csv file on GitHub. Doing this will make your life a lot easier, especially when regularly changing the dataset you are using. …
For those of you that have started learning Python, it can be daunting to start a project, as most of what you see about it is probably related to data science or machine learning.
If you are in that situation and want to practice your newly acquired skills, why not build a Snake game? All you need to know for this tutorial is loops (for, if and while), lists and functions.
Well, if you are convinced then let’s jump ahead.
Snake is a video game that first appeared in 1976. …