#tensorflow #cuda #objectdetection #gpu #rtx #nvidia

I guide you step by step on how to setup Deep Learning with Tensorflow on a PC with an Nvidia RTX 3070 and a Ryzen 5900 CPU in Windows 10.

IMPORTANT: In addition to the video, if your Tensorflow doesn’t detect your GPU and you get the following error:

Could not load dynamic library ‘cusolver64_10.dll’; dlerror: cusolver64_10.dll not found

If you are using CUDA 11.2, just go to “C:Program FilesNVIDIA GPU Computing ToolkitCUDAv11.2bin” and copy and paste cusolver64_11.dll and rename it cusolver64_10.dll.
That should solve the error.

Article: https://spltech.co.uk/building-my-first-pc-for-deep-learning/
Tensorflow Documentation: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/install.html

Timestamps:

0:00 Introduction
1:30 Installing Anaconda with Python 3.7
2:47 Creating Conda environment for Tensorflow with Python 3.8(using conda create and conda activate)
3:29 Installing Tensorflow 2.2.0 and verifying Tensorflow installation(1st attempt)
4:15 Tensorflow doesn’t detect CUDA, which is needed if I want to use the GPU
4:30 Installing CUDA 11.2
6:22 Difference between CUDA cores and CPU cores
9:30 Testing Tensorflow 2.20 to see if it can work with my GPU
11:00 Installing Tensorflow 2.3.0 to see if it can work with CUDA 11.2
11:50 Installing Tensorflow 2.4.0 and it works with CUDA 11.2!
12:40 Installing cuDNN
15:00 Installing Object Detection API
15:37 Installing Protobuf 3.12.3
18:50 Installing Visual Studio
19:30 Testing that the object detection API works

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