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How to install Tensorflow 2.5 and CUDA 11.2 with a CPU and a GPU on Windows 10

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#tensorflow #deeplearning #cuda #gpu #rtx30 #rtx3060 #rtx3070 #rtx3080 #rtx3090 #amd
How to install Tensorflow 2.5, CUDA 11.2.1, and CuDNN 8.1, for Windows 10, with full deep learning support for an Nvidia GPU RTX 30 series card, like the Nvidia RTX 3060, RTX 3060TI, RTX 3070, RTX 3080, and RTX 3090. Since CUDA is backward compatible it should also work for RTX 20 series cards or older.
But before I install CUDA, I will do some benchmarking of Tensorflow 2.5 without a GPU. I will be training an image classification model that I developed in a previous video, with my AMD Ryzen 5900X CPU.
The AMD Ryzen 5900X CPU has 12 cores and 24 threads, and it is a decent CPU all around, perfect for a beginner in Deep Learning like myself.
Once I complete the CUDA setup, I will try again to complete the training of the same model with my Nvidia RTX 3070 GPU. It has 5888 CUDA cores. Can it beat the AMD Ryzen 5900X CPU? It definitely should.
✅ Recommended Courses
(Includes Amazon Affiliate Links)
==================================
✅ Recommended Playlists
==================================
✅ My Favorite Tech
(Includes Amazon Affiliate Links)
==================================
✅ My RTX 3070 and Ryzen 5900 Machine Learning PC Build
(Includes Amazon Affiliate Links)
=======================================================
As an Amazon Associate, I earn a small commission from qualifying purchases on the amazon links above. It costs you nothing but helps me in keeping the content coming.
✅ ARTICLE
✅ BUSINESS ENQUIRIES
✅ SUPPORT ME
✅ TIMESTAMPS
0:00 Introduction
2:15 Installing Anaconda
3:18 Installing latest Nvidia Game-Ready graphics driver
3:49 Creating new Anaconda environment for Tensorflow 2.5
4:30 Installing Tensorflow 2.5 rc 1 with pip, matplotlib and pandas
6:00 Installing JupyterLab from Anaconda
6:45 Testing Tensorflow model training works with my AMD Ryzen 5900X CPU
10:00 Reviewing training times for Tensorflow with the Ryzen 5900X CPU
11:40 Installing CUDA 11.2.1
12:08 Installing cuDNN 8.1
13:00 Copying cuDNN files to CUDA folder
15:00 Setting CUDA environment variable
16:00 Test Tensorflow model training with my RTX 3070 GPU
17:49 Compare GPU vs CPU for Deep Learning
How to install Tensorflow 2.5, CUDA 11.2.1, and CuDNN 8.1, for Windows 10, with full deep learning support for an Nvidia GPU RTX 30 series card, like the Nvidia RTX 3060, RTX 3060TI, RTX 3070, RTX 3080, and RTX 3090. Since CUDA is backward compatible it should also work for RTX 20 series cards or older.
But before I install CUDA, I will do some benchmarking of Tensorflow 2.5 without a GPU. I will be training an image classification model that I developed in a previous video, with my AMD Ryzen 5900X CPU.
The AMD Ryzen 5900X CPU has 12 cores and 24 threads, and it is a decent CPU all around, perfect for a beginner in Deep Learning like myself.
Once I complete the CUDA setup, I will try again to complete the training of the same model with my Nvidia RTX 3070 GPU. It has 5888 CUDA cores. Can it beat the AMD Ryzen 5900X CPU? It definitely should.
✅ Recommended Courses
(Includes Amazon Affiliate Links)
==================================
✅ Recommended Playlists
==================================
✅ My Favorite Tech
(Includes Amazon Affiliate Links)
==================================
✅ My RTX 3070 and Ryzen 5900 Machine Learning PC Build
(Includes Amazon Affiliate Links)
=======================================================
As an Amazon Associate, I earn a small commission from qualifying purchases on the amazon links above. It costs you nothing but helps me in keeping the content coming.
✅ ARTICLE
✅ BUSINESS ENQUIRIES
✅ SUPPORT ME
✅ TIMESTAMPS
0:00 Introduction
2:15 Installing Anaconda
3:18 Installing latest Nvidia Game-Ready graphics driver
3:49 Creating new Anaconda environment for Tensorflow 2.5
4:30 Installing Tensorflow 2.5 rc 1 with pip, matplotlib and pandas
6:00 Installing JupyterLab from Anaconda
6:45 Testing Tensorflow model training works with my AMD Ryzen 5900X CPU
10:00 Reviewing training times for Tensorflow with the Ryzen 5900X CPU
11:40 Installing CUDA 11.2.1
12:08 Installing cuDNN 8.1
13:00 Copying cuDNN files to CUDA folder
15:00 Setting CUDA environment variable
16:00 Test Tensorflow model training with my RTX 3070 GPU
17:49 Compare GPU vs CPU for Deep Learning
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