Pluralsight Path Deep Learning Literacy Practical Application 2022 C1 Implement Natural Language Processing for Word Embedding Axel Sirota 2022 Fine tuning Word Representations Demo Fine Tuning Glove and FastText vtt

Pluralsight Path Deep Learning Literacy Practical Application 2022
C1 Implement Natural Language Processing for Word Embedding Axel Sirota 2022 Fine tuning Word Representations Demo Fine Tuning Glove and FastText vtt

Name	Pluralsight Path. Deep Learning Literacy. Practical Application (2022)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.9 GB
Total Files	486
Last Seen	2025-04-06 23:42
Hash	834B6201E4DFFFCAA866824648C67D3D42C40431

/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/2. Demo - Fine Tuning Glove and FastText.vtt	13.3 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/2. Demo - Fine Tuning Glove and FastText.mp4	67.6 MB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/3. Demo - Making Word Clusters.vtt	7.8 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/3. Demo - Making Word Clusters.mp4	21.4 MB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/4. Demo - Debiase Word Embeddings.vtt	9.6 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/1. Why Would We Fine Tune Existing Models.vtt	2.5 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/5. Key Takeaways and Tips.vtt	1.1 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/6. Where to Go Next.vtt	1.8 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/4. Demo - Debiase Word Embeddings.mp4	40.3 MB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/4. Demo - Analyzing Sentiment with OHE.vtt	8.3 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/1. Why Would We Fine Tune Existing Models.mp4	3.8 MB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/5. Key Takeaways and Tips.mp4	1.7 MB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/6. Where to Go Next.mp4	4.2 MB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/6. Demo - Training a CBOW Embedding.vtt	14.6 KB
/C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/3. Demo - Using OHE.vtt	11.5 KB
Showing first 15 files of 486 total files