Heartbeat

JANUARY 13, 2024

Quick Summary In this article, I’ll show you how to create amazing images from audio using the magic of Machine Learning and the Transformers models. In this guide, I will demonstrate how to generate images from audio using pre-trained models. You can learn more about the model here. Now, we’re going under the hood.

Machine Learning 52

Machine Learning NLP Python Deep Learning 52

AWS Machine Learning Blog

DECEMBER 14, 2023

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart , a machine learning (ML) hub offering models, algorithms, and solutions. Stable Diffusion is a text-to-image model that empowers you to create high-quality images within seconds.

Natural Language Processing 96

Natural Language Processing LLM Prompt Engineer Prompt Engineering 96

deepsense.ai

OCTOBER 8, 2023

External sources of informationA way to interact with the user (an optional feature) Attempts have been made to create agents in various fields such as: Robotics: Agents can range from simple automated machines to complex humanoid robots designed to assist or replace humans in various tasks.

Auto-complete 92

Auto-complete LLM AI AI 92

AWS Machine Learning Blog

FEBRUARY 19, 2024

This architecture includes the following steps: A user interacts with the Streamlit chatbot interface and submits a query in natural language This triggers a Lambda function, which invokes the Knowledge Bases RetrieveAndGenerate API. You need to clone the GitHub repository to your local machine.

Chatbots 101

Chatbots Data Ingestion Machine Learning Generative AI 101

AWS Machine Learning Blog

NOVEMBER 7, 2023

Without continued learning, these models remain oblivious to new data and trends that emerge after their initial training. Amazon Kendra with foundational LLM Amazon Kendra is an advanced enterprise search service enhanced by machine learning (ML) that provides out-of-the-box semantic search capabilities.

Large Language Models 96

Large Language Models Generative AI LLM AI 96

AWS Machine Learning Blog

SEPTEMBER 19, 2023

Quantitative modeling and forecasting – Generative models can synthesize large volumes of financial data to train machine learning (ML) models for applications like stock price forecasting, portfolio optimization, risk modeling, and more. He guides customers to design and engineer Cloud scale Analytics pipelines on AWS.

Generative AI 104

Generative AI LLM Python Large Language Models 104

AWS Machine Learning Blog

MAY 1, 2024

Our unstructured data comes from the Amazon EC2 User Guide for Linux Instances and Amazon EC2 Instance Types documentation, and the structured data is derived from the EC2 Instance On-Demand Pricing for the US East (N. Virginia) AWS Region. The following diagram illustrates the solution architecture. xlarge instance to $24.78

Chatbots 101

Chatbots Automation Machine Learning DevOps 101

Mlearning.ai

MARCH 15, 2023

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. Web App Development : Build a web app using Streamlit and Python to interact with the deployed model and display the predictions.

Python 52

Python Machine Learning Data Extraction Data Analysis 52

AWS Machine Learning Blog

MAY 3, 2023

This is where the highly accurate, machine learning (ML)-powered intelligent search in Amazon Kendra plays an important role. You can deploy this solution in your AWS account using the step-by-step guide in this post. If you want to use the sample web apps built using Streamlit , you first need to install Streamlit.

Large Language Models 68

Large Language Models Generative AI LLM Chatbots 68

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Nice to have you here, Miki.

ML 52

ML Data Scientist Machine Learning Data Science 52

AWS Machine Learning Blog

APRIL 24, 2024

It consists of the following key components: Conversational interface – The conversational interface uses Streamlit, an open source Python library that simplifies the creation of custom, visually appealing web apps for machine learning (ML) and data science. Additionally, you can access device historical data or device metrics.

Conversational AI 111

Conversational AI LLM AI AI 111

AWS Machine Learning Blog

FEBRUARY 14, 2024

Prompt engineering Prompt engineering is the process where you can create and design user inputs that can guide generative AI solutions to generate desired outputs. We then send this enriched prompt to an LLM, specifically, Anthropic’s Claude on Amazon Bedrock, to obtain a customized travel plan.

Prompt Engineer 118

Prompt Engineer Prompt Engineering Generative AI AI Chatbots 118

Bugra Akyildiz

SEPTEMBER 4, 2023

Libraries like Streamlit and Gradio have considerably simplified building applications for ML models. Google Research wrote a blog post explaining introduction of a new method for pre-training vision transformers for open-vocabulary object detection. Contrastive learning: RO-ViT is trained using a contrastive learning approach.

Large Language Models 52

Large Language Models ML Python LLM 52

Heartbeat

AUGUST 9, 2023

Comet: A Machine Learning Platform for Keeping Track of Our Model Overview This is a well-detailed step-by-step guide on creating a computer vision application in 10 steps using comet_ml and streamlit. Now that you have downloaded the flower_photos file, unzip and save the file on your local machine.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Python 52

The MLOps Blog

MARCH 21, 2023

Moving across the typical machine learning lifecycle can be a nightmare. Machine learning platforms are increasingly looking to be the “fix” to successfully consolidate all the components of MLOps from development to production. That’s where this guide comes in! What is a machine learning platform?

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69