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ML - machine learning

This is just a documentation of my learning progress. Inspired by object detection for cars with DarkNet (see this TED talk from 2017 by Joseph Redmon) and David’s bachelor work at HCMUTE in connection with a car at the end of 2018 I started to learn more about machine learning.

Posenet runs on TensorFlow.lite in a browser on WebGL even on a smartphone. We tested it in December 2018 in Seoul, Korea. In March 2019 I got TensorFlow.js running with my RX470 with 43 fps.

Posenet the park

During 2019 NVIDIA announced the Jetson Nano developer kit and with students from AISVN we try to win one in a competition. Eventually we order a package.

Jetson Nano car

Early 2020 some supply chains delay orders, but we finally have the hardware. Now it needs to be combined - and development stalls until 2024.

Facemesh example

Facemesh example

Schedule

In this article Harsheev Desai describes his journey to become a TensorFlow Developer with Certificate in 5 months.

1. Learn Python

2. Learn Machine Learning Theory

3. Learn Data Science Libraries

Some of these libraries are Pandas (data manipulation and analysis), Numpy (support for multi-dimensional arrays and matrices), Matplotlib (plotting) and Scikitlearn (creating ML models).

4. Deep Learning Theory

5. TensorFlow Certificate

One reason for tensorflow can be seen in this graph regarding popularity on stack overflow:

popularity tensorflow

More about the certificate here on medium. It was introduced in March 2020 but by 2024 it no longer exists.

History