D4Darious:
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D4Darious:
Rendered using an RTX 3090
Below are my notes and setup and screenshots as l configured my system for using and exploring Pytorch.
I used:
Reference link used – click here:
Screenshots
RTX Series card are used mainly for content generation, but the relative cost per internal hardware has also made it in demand for bitcoin mining and – in my interest area – Artificial intelligence [AI]/machine learning [ML] as per the tensor cores found in them. They are also used for gaming PC’s – the least of my application area.
Got below text from a friend, P.I – and ended up heading to Cascade Station Bestbuy where l stayed overnight [about 10+ hours] in line, with lots of other people, waiting for Nvidia RTX cards to be handed out for purchase first come first served at MSRP the following 8am.
Street prices for these cards have been about 3-4X MSRP online since early 2020 when Nvidia released the RTX lines.
Got here about 7pm July 19th, got my RTX 3xxx card 8am on July 20th
Pictures and video clips below.
Trying to resolve below, using the information from this link – click here.
Download and install:
Setup screenshots:
Some screenshots showing basic C++ step debugging, of a UE4 [ Unreal Engine] C++ project, using Visual Studio which opens up the solution file.
F11 for Stepping through.
Left Clicking the bar next to the code line number turns it to a breakpoint, indicated by the red circle.
“The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language.” Source Wikipedia
Setup and test screenshots below:
Text:
import nltk
nltk.download()
from nltk.corpus import names
print(names.words()[:200])
print(len(names.words()))
Test run output to verify installation:
Using this further:
… coming soon