By following the TensorFlow guide, it is easy to see how TensorFlow harnesses the power of my new Nvidia RTX 2060.
The first one is image recognition. Similar to the technology used in a previous installment on neural network training with traffic images from CCTV captured, a sample data set of images with classification of fashion objects are learnt by using TensorFlow. In that previous installment, Amazon Web Service cloud with a K520 GPU instance is used for the model training. In this blog post, the training is actually taking place in the Nvidia RTX 2060.
Another classic sample is the regression analysis, from the Auto MPG data set. With a few line of code, TensorFlow clean up the data set to remove unsuitable values and convert categorical values to numeric ones for the model.
The TI Nspire calculator is a great platform for visualizing data via interactive graphs. The built-in facility like input slider for variable value adjustment allowed dynamic visualization to complex equations, like the volatility sensitivity in delta-hedged gains used financial investment. Since this strategy involved a single call option, the volatility exposure equals the vega value of the option.
The following setup on the Nspire provided the functions to calculate the vega values.
This spreadsheet input screen stores the spot prices and the calculated Black Scholes vega values.
Finally, with the data plotting screen the graph of Delta hedged gains of volatility sensitivity is completed. An additional slider control can easily be added on it to adjust an offset variable so as to visualize scenarios under different spot price.
On my desk there is an IoT device that measures temperature and log data to the Internet. It is a hobby project build with Texas Instruments MSP430 series MCU, with an IR temperature sensor TMP006 (Infrared Thermopile Contactless Temperature Sensor) also from TI.
The temperature data are published via an OpenWRT TP-Link router to Exosite which is running a partnership program with TI on IoT services.
Last night I noticed something I never noticed before – a clear pattern of a less fluctuating period (around 19:00 to 21:00).
Possible cause: I turned off the fan to go dine out. When I’m back the fan is back on, added to the environmental factor that my body temperature and the turbulence from the fan lead to the fluctuation – just wild guess, it’s weekend 🙂