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Machine Learning Courses @UCVvso8xTYp9Et6wBXELd2Wg@youtube.com

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05:39
Testing our Sagemaker Model with Postman, AWS Api Gateway and Lambda
10:17
Analyzing AWS Sagemaker Model Load Test Results
08:55
Deploying our FineTuned LLM to Sagemaker
05:47
Analyzing AWS Sagemaker Training Job Results in CloudWatch
05:40
Understanding the Mathematics Behind Cross Entropy Loss(for LLMs)
17:15
Modify the Architecutre of LLMs in Sagemaker with PyTorch
15:06
Understanding the Tokenization Vocabulary of LLMs
11:08
Data Visualization with AWS Sagemaker
18:35
Deploy a HuggingFace Sentiment Analysis Model on AWS Sagemaker
22:00
Calculating Raw Attention Scores for Attention Mechanisms in LLMs and Transformers
18:21
Query, Key and Value Matrix for Attention Mechanisms in Large Language Models
09:33
Converting Raw Attention Scores to Probability Distributions with the Softmax Function
13:57
Understanding the mathematics Behind Dot products and Vector Alignment for Attention Mechanisms
09:36
Visualizing Positional Encodings in Sine and Cosine Graphs
09:01
Understanding Tokenization for LLMs with Python code
11:25
Tokenization for Large Language Models like ChatGPT and other Transformers
06:24
LLM Evaluation with AWS Bedrock Understanding our Evaluation Report
07:32
Retrieval Augmented Generation(RAG) in AWS Bedrock with LLMs
12:06
AWS Bedrock Inference Configurations for LLMs and Diffusion Models for Generative AI
09:58
Summarise your Meeting Notes with AWS Bedrock, Generative AI
10:31
AWS Bedrock Introduction
07:02
Serverless architecture with AWS Bedrock for Generative AI
09:08
AWS Bedrock Generative AI: Train your own LLM with your own data
15:22
Visualizing Multiple Images with Matplotlib in AWS
11:16
Data Augmentation for Object detection in AWS Sagemaker
13:12
Setup AWS Step Functions for a Machine Learning pipeline in AWS
21:08
Hyperparameter Tuning with AWS Sagemaker
08:51
Using AWS Eventbridge to set up Cron jobs for our Machine Learning Pipeline in AWS
07:20
Starting a Batch Transformation Job for Object detection in AWS Sagemaker
00:27
Data Visualization with Plotly in SageMaker(Random Cut Forest)
07:48
Evalaute your SageMaker machine learning training job in Cloudwatch
04:27
Use AWS API Gateway, Lambda functions, and Postman to Invoke Machine Learning models in AWS
05:04
Use Kaggle API to download data to AWS SageMaker Notebook for Machine Learning
04:17
How to set up Lambda Concurrency in AWS
02:49
AWS, React,Next.js,Node.js Machine Learning model in production. Testing in production
02:27
Deploy Production ready Scalable Machine Learning models with AWS , React, Node.js and DigitalOcean