Data science

First of all, I want to thank you. The first article has skyrocketed on Medium and Twitter (more than 15k views and 350 claps). I am grateful for it. I want to thank you all for the support. As promised, here the second part.

Let’s go back on what we have seen so far.

Before to start, I recommend you to read the first part published on TDS, to get a first overview of the first characters, as different characters in this article will referring to it:

Along with this article, we will explore remaining characters from David Benioff and…

This article is going to be a bit special. I am going to test the latest release from Yahoo Finance API for Python, which provide the possibility to get live data with less than a second lag for free.

In this article, you will learn how to get live Forex data, using Python packages without calling an expensive API such as Bloomberg. I have tested it for you. Does that work? Let’s see.

If you are keen to hack it yourselves now, you can get the full Python code at the end of this article.

You will be able to…

Data Science & Python for beginners.

If you’ve ever worked on a personal data science project, you’ve probably spent a lot of time browsing the internet looking for interesting datasets to analyze.

Even if that can be fun to sift through dozens of datasets to find the perfect one, it can also be frustrating to download and import several CSV files to realise that the data isn’t interesting after all.

On top of that, making your data science journey more fun is crucial for your progress, and keeps your motivation high.

I firmly believe that you will always be more efficient if you enjoy what you…

Wall street

Everything started early January 2021. On this day, a historic brand for video game enthusiasts, the GameStop channel, which is far from offering a shining model of growth in an era when online shopping, have seen an army of geeks and small investors willing to spread blood on wall street barons, giving them protection.

Data Science for Algorithmic Trading

In this article, we will discover how to download cryptocurrency data in real-time (+/- 0.1 seconds lag), using a Yahoo Finance API. I have tested it for you. Does that work? Let’s see.

If you are keen to hack it by yourselves now, you can get the full Python code and tutorial video which I recorded for you, at the end .

Along with this article, you will be able to get cryptocurrency market data such as price, volume and fundamental data using Python packages. (With less than 0.1 seconds lag).

If you want to extend your knowledge on how…

Python for Algorithmic Trading

According to Google Trend, Bitcoin is officially one of the most trendy search terms of 2021. Between October 2020 and January 2021, the number of research for “Bitcoin” has been multiplied by 11. And the number of people using the search term “bitcoin vault” increased by 3,500%. (Source)

As data enthusiastic, we must keep ourself up to date. That’s why I have been researching a simple way to get cryptocurrency fundamentals data updated each second.

In this article, we will discover how to download cryptocurrency data in real-time (+/- 0.1 seconds lag), using a Yahoo Finance API. I have tested…

Algorithmic Trading — Full guide

The mathematical algorithm which we are going to use is called Bollinger Bands.

First of all, if you want to go further about science and algorithmic trading, I highly recommend you to take a look at this complete guide:

Ok let’s start!

The Bollinger Bands

Bollinger Bands are an indicator of volatility.

They are based on the correlation between the normal distribution and the evolution of a share’s value.

As a result, Bollinger Bands can draw a support curve and a resistance curve that will frame the evolution of a share value.

The Normal Distribution :

The normal distribution is a probability distribution that describes that values…

Full guide

A training set is implemented in a dataset to build up a model, while a test (or validation) set is to validate the model built. Data points in the training set are excluded from the test (validation) set. Usually, a dataset is divided into a training set, a validation set (some people use ‘test set’ instead) in each iteration, divided into a training set, a validation set and a test set in each iteration.

In Machine Learning, we basically try to create a model to predict the test data. So, we use the training data to fit the model and…