Resource of free step by step video how to guides to get you started with machine learning.
Thursday, March 12, 2020
Learning to read with TensorFlow and Keras (TF Dev Summit '20)
Natural Language Processing (NLP) has hit an inflection point, and this talk shows you how TensorFlow and Keras make it easy to preprocess, train, and hypertune text models. Speaker: Paige Bailey - Product Manager Resources: The Goldilocks Principle → https://goo.gle/2PPUmBi GitHub Keras Preprocessing Layers → https://goo.gle/2uWFqKm GitHub Keras Preprocessing API → https://goo.gle/38ohwoU Understanding Encoder-Decoder Sequence to Sequence Model → https://goo.gle/2IsPtde Keras Tuner documentation → https://goo.gle/2InBK7J Hyperparameter tuning with Keras Tuner → https://goo.gle/2VPtMvR TensorFlow Text → https://goo.gle/2TueZVV GitHub Bert → https://goo.gle/2xhNQgm TensorFlow Hub breakdown → https://goo.gle/2wAwbQy Watch all TensorFlow Dev Summit 2020 sessions → https://goo.gle/TFDS20 Subscribe to the TensorFlow YouTube channel → https://goo.gle/TensorFlow
Labels:
Video
Published by Free artificial intelligence and machine learning video tutorial resource
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 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: 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: Yes, for most budget builders: a used RTX 3090 is still the cheapest route to 24 GB of VRAM with full CUDA support. Capacity...
-
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...
-
Quick answer: DeepSeek V4 Flash is a Mixture-of-Experts model: all 284 billion parameters must be stored, so combined RAM plus VRAM — not ...
-
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...
No comments:
Post a Comment