Resource of free step by step video how to guides to get you started with machine learning.
Friday, July 12, 2019
TensorFlow.js (TensorFlow Meets)
TensorFlow.js (TensorFlow Meets)
[Collection]
On this episode of TensorFlow Meets, Laurence (@lmoroney) talks with Yannick Assogba, Front End Software Engineer on the TensorFlow team. Learn about how to get started with TensorFlow.js as the 1.0 version is now available. Comment below for any questions!
This video is also subtitled in Chinese, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish.
TensorFlow.js → http://bit.ly/2L6Bq0k
TensorFlow.js 1.0 (TF Dev Summit ‘19) → http://bit.ly/2S74ohl
BodyPix - person segmentation in the browser → http://bit.ly/30iFI8z
Toxicity classifier → http://bit.ly/2NQfkBk
Universal sentence encoder → http://bit.ly/2LKiHHq
Subscribe to the TensorFlow channel → https://goo.gle/2WtM7Ak
Watch more episodes of TensorFlow Meets → https://goo.gle/2Z8zCXJ
Labels:
TensorFlow
Published by Free artificial intelligence and machine learning video tutorial resource
Location:
TensorFlow.js (TensorFlow Meets)
Related video tutorials
Subscribe to:
Post Comments (Atom)
Most watched
-
Quick answer: Qwen 3 32B needs about 22.7 GB of VRAM at Q4_K_M with a 4k-token context — a used 24 GB card like the RTX 3090 is the minimu...
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
Inside TensorFlow: Summaries and TensorBoard [Collection] Take an inside look into the TensorFlow team’s own internal training sessions-...
-
Quick answer: For an 8B model at Q4, local electricity costs roughly $0.05 per million output tokens — against about $0.53 per million ble...
-
Quick answer: For machine-learning work, buy an external SSD over a spinning hard drive, pick USB 3.2 Gen 2 (10 Gbps) or faster, and size f...
-
Quick answer: DeepSeek V4 Flash is a Mixture-of-Experts model: all 284 billion parameters must be stored, so combined RAM plus VRAM — not ...
-
Quick answer: Yes, for most budget builders: a used RTX 3090 is still the cheapest route to 24 GB of VRAM with full CUDA support. Capacity...
-
Hey everyone This is Ujjwal kapil B.tech 2nd year Ai and Ml In this video we covered one of the most important question "COLLEGE KAB O...
-
Quick answer: The cheapest path to serious local-AI VRAM is not one new flagship card — it is two used ones. A single RTX 5090 costs $1,999...
-
Quick answer: FLUX.1 dev needs about 10 GB of VRAM at Q4/NF4 quantization for 1024×1024 image generation, so a 12 GB GPU such as the GeFor...
No comments:
Post a Comment