I have read a book “Deep Learning with Python” by Francois Chollet.
[Deep Learning with Python][/url]
Mr. Chollet is the creator of the Keras deep learning library.
His book is excellent, even if it was published in 2017.
My development platform is the Nvidia Jetson Nano 4.2.2 and it rocks.
I have posted a couple of times about challenges I have had learning the system.
I want to relocate my posts in one place so it makes better sense.
“Nano Faster” is the new topic area for my past posts, as soon as I can figure out how
to move them…Stay tuned…or advise me how to do the move.
Thanks in advance
Kent
My goal was to build the Jetpack4.2.2 on a 64 GB SD Card for the Nano Development System.
I used the SDK Manager to install Jetpack4.2.2 on a 64 GB SD Card.
The result was an APP partition of 14 GB as the first partition.
The remaining partitions were installed following the APP partition and before the un-allocated space or approximately 45 GB at the end of the sd card space.
The Nano Development Board booted up but quickly ran out of SD Card storage.
Because the APP was first and the other small partitions immediately followed, no partition tool I
tried could resize APP to more then 14 GB.
I started from scratch and created the SD card system manually, not using the SDK Manager.
The partition order was all small partitions came first, with APP being last with un-allocated space adjacent to APP. gparted resized the APP partition to approximately 63 GB.
Everything worked great.
My request is to free up development from requiring an SD Card based Boot and Storage media.
Instead, enable the SDK Manager to format USB attached NVME SSD storage like the Intel 660p, etc.The Intel 660p I used is contained in a Pluggable NVME SSD case that attaches to USB3 or USBC, etc. It works fine with the Nano Development system USB3 ports.
Anybody have any ideas?
Thank you in advance.