Automated Drone Flight: Circular Flight
In this post, we are programming a more complex non-interactive flight mission for a TELLO EDU drone. As a foundation, we are using the...
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H-Barrio
- Aug 18, 2021
Automated Drone Flight: Recording - Systems at Scale
It often makes sense to test large and complex systems using smaller scale models. Automotive, aerospace, and to a lesser extent,...
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H-Barrio
- Jul 27, 2021
Natural Resources as Stock Market Trouble Alarm
Stock markets shocks are notoriously difficult to predict. In general, periods of high volatility can lead to both large market gains and...
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H-Barrio
- Jul 20, 2021
Regression with a Random Neural Network
It is time to put our randomly generated Deep Neural Networks (DNNs) to the test. These neural networks, left to chance due to our...
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H-Barrio
- Jul 13, 2021
Deep Neural Network: Left to Chance
Designing the architecture of a deep neural network is difficult. There are multiple decisions to be made regarding the network...
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H-Barrio
- Jun 29, 2021
Checking Inside (Drone) Videos and Frame Splits
In this post, we will quickly check the information really contained in the video files produced by digital recording systems and obtain...
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H-Barrio
- Jun 22, 2021
Thousands of Hours Away, On the Right Track
In some cases, it is necessary to conduct a rapid survey of the data obtained from source data without devoting too much development...
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H-Barrio
- Jun 15, 2021
Storing Map Tiles for Offline Use: HTML to JPG in Jupyter Notebooks
To finish exploring the possible uses for geographic source data for the obtention of intelligence (covered in this post and this post),...
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H-Barrio
- Jun 8, 2021
Mapping GEO Data with Folium
Map generation from geographic data.
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H-Barrio
- Jun 1, 2021
Primary Data Sources: Geographical Data from WFS
Data is the new oil. Data is the new gold. The mithril of Moria. These phrases are used to emphasize the value of data in the current...
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H-Barrio
- May 25, 2021
Correlation Index: Momentum and Volatility Checks
Our attempt at using the correlation index as a trading signal did not generate very good results. After optimizing for historical...
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H-Barrio
- May 18, 2021
Correlation Index Using a Parameter Grid
In our last analysis, we found that the correlation index for the top traded stocks in the SPY index could potentially contain...
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H-Barrio
- May 11, 2021
Correlation Index at the Top (II)
We have seen that there are times when those companies at the top of the SPY index in terms of capitalization move in lockstep and times...
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H-Barrio
- May 4, 2021
Correlation Index at the Top of the SPY
SPY correlation index for the recent past. Can stock movements be predicted by the returns correlation of the most capitalized companies?
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H-Barrio
- Apr 27, 2021
State of the ETHEUR to BTCEUR Ratio
Cryptocurrencies are new assets compared to traditional means of exchange and stores of value. The ratio of the prices of the two most...
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H-Barrio
- Apr 20, 2021
Visual Flow Representation of Stock Market Data
Today we revisit our very first post on the application of visual pattern recognition methods to stock market price predictions. This...
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H-Barrio
- Apr 13, 2021
Interlude: Automated UML Model with Python
This is an interlude to our usual topics. This post will be one level inside quantitative model development, one level below using a...
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H-Barrio
- Apr 6, 2021
CUSUM Event Identification: Not Just for Sampling
Cumulative sum filtering is a signal sampling method presented in Marcos Lopez de Prado. 2018. Advances in Financial Machine Learning...
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H-Barrio
- Mar 30, 2021
Entropy Based Label Selection
Now we have a tool that will flexibly obtain labels for our hypothetical trading positions, all of them inside a certain space of future...
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H-Barrio
- Mar 23, 2021
DataFrame-Ready Implementation for Triple Barrier Labels
We will continue adapting the methods presented in Marcos Lopez de Prado. 2018. Advances in Financial Machine Learning (1st. ed.). Wiley...
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