179.6 MB | 00:04:00 | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English
Files Included :
01-selecting foundation models.mp4 (11.71 MB)
02-inference parameters.mp4 (7.72 MB)
03-retrieval-augmented generation rag.mp4 (4.98 MB)
04-vector storage solutions on aws.mp4 (6.18 MB)
05-cost tradeoffs for customization.mp4 (8.37 MB)
06-agents for multi-step tasks.mp4 (5.11 MB)
07-exam tips.mp4 (8.77 MB)
01-fundamentals of prompt engineering.mp4 (12.33 MB)
02-prompt engineering techniques.mp4 (13.03 MB)
03-benefits and best practices.mp4 (5.94 MB)
04-risks and limitations of prompt engineering.mp4 (5.73 MB)
05-exam tips.mp4 (6.17 MB)
01-key elements of training foundation models.mp4 (5.48 MB)
02-methods for fine-tuning foundation models.mp4 (3.54 MB)
03-preparing data to fine-tune a foundation model.mp4 (6.74 MB)
04-exam tips.mp4 (5.77 MB)
01-evaluation approaches for foundation models.mp4 (4.36 MB)
02-performance metrics.mp4 (8.56 MB)
03-business objective alignment.mp4 (3.59 MB)
04-exam tips.mp4 (4.49 MB)
01-design considerations for foundation models.mp4 (4.12 MB)
02-prompt engineering techniques.mp4 (3.11 MB)
03-training and fine-tuning foundation models.mp4 (2.89 MB)
04-evaluating foundation model performance.mp4 (4.05 MB)]
Screenshot
Code:
https://rapidgator.net/file/c65a42b33b601c2e81b7bd152dd15593/
Code:
https://turbobit.net/de4mnpyaz55y.html