AWS SageMaker AI technology page Top Builders

Explore the top contributors showcasing the highest number of AWS SageMaker AI technology page app submissions within our community.

AWS SageMaker

Amazon SageMaker is a fully-managed machine learning service that makes it easy for data scientists and developers to quickly and easily build, train, and deploy models into a production-ready hosted environment. It provides an integrated Jupyter notebook instance for convenient access to data sources for exploration and analysis, eliminating the need to manage servers. Additionally, it offers optimized common machine learning algorithms that are designed to function efficiently with large data sets in distributed environments. SageMaker also allows users to bring their own algorithms and frameworks and offers flexible distributed training that can be adapted to individual workflows. Models can be quickly deployed into a secure and scalable environment using the SageMaker Studio or the SageMaker console.

General
Relese date	November 29, 2017
Author	AWS
Type	Learning Service

AWS Amazon SageMaker Libraries

Discover the AWS Amazon SageMaker libraries and SDKs.

AWS Amazon SageMaker Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows
SageMaker Tutorials Machine Learning Tutorials with Amazon SageMaker

Edit on Github

AWS SageMaker AI technology page Hackathon projects

Discover innovative solutions crafted with AWS SageMaker AI technology page, developed by our community members during our engaging hackathons.

Autilent

Autilent is a smart solution that is capable of automatically detecting high risk situations during driving and then helps eliminate them. A special device powered by autilent's proprietary AI algorithms is installed inside the cabin of the vehicle. This device has two cameras, driver facing and road facing. The video feed is analysed in realtime by our in-car processor and the system then detects potential accident-causing actions e.g distractions, drowsiness, mobile phone usage etc. Realtime alerts are then generated to warn the drivers and alert the command and control centres in order to take preventative action. Additionally, we also offer data driven insights into every individual driver's behaviour and give hyper-personalised recommendations in order to bring a positive change in the driver behaviour and make them safer on the roads. We are on a mission to save lives and resources and look forward to your support in this. In the demo, please select the dates 1-15th March, and the driver: Saad Farooq, and in the vehicle section, KSA-006

Weaviate Blogs QA Chatbot prototype

[Weaviate Blogs QA Chatbot Prototype by R2 Rapid Response Team] Providing users simple question answering chatbot interface over Weaviate's blogs posted in 2023 to catch up on vector database and generative AI trends and get relevant information grounded on Weaviate's excellent blog postings in 2023 as a data source. LangChain template is used for rapid prototyping with LangServe and LangSmith for production ready prototype build. Hybrid search offers best part of both world by offering a combination of keyword search and semantic search on top of Cohere's Reranker to provide optimum search results and improve user experience. Future roadmap includes front end UI for end users with a feedback loops as documented in one of Weaviate's blog posting. Behind the scenes, we've turbocharged this rapid prototype with Weaviate's hybrid search capabilities. The combination of semantic and keyword search surfaces optimum results from the corpus of blog content. In addition, Cohere's reranker helps picking the best excerpts. The rapid prototype was possible thanks to LangChain templates, LangServe, and LangSmith. This allows us to deliver a production-ready user experience on an accelerated timeline. Looking ahead, our roadmap includes building out a frontend UI for end users and implementing feedback loops to continuously improve the experience. But even in its current form, this prototype enables anyone to tap into Weaviate's blogs like never before. Just ask a question, and the knowledge is at your fingertips. In closing, I'm excited by the potential for this conversational interface to open up new ways to share Weaviate's thought leadership. Thank you for considering our Weaviate Blogs QA Chatbot submission. I welcome any questions you may have. Thank you.

FitMate AI - Falcon ARG

FitMateAI is more than just a fitness web app. It's a wellness companion that harnesses the power of cutting-edge AI to redefine how individuals approach their fitness and nutrition journey. Our platform provides users with highly personalized workout programs and expert dietary plans, meticulously crafted based on their unique inputs. Our mission is to empower individuals to take charge of their fitness and wellness goals through the guidance of intelligent technology. We recognize that the fitness industry bombards people with generic workout routines and nutrition advice, and this can be frustrating and counterproductive, leading to plateaus and, in some cases, the abandonment of fitness routines. In a world where health and wellness are increasingly paramount, FitMateAI provides the perfect solution. It's not just about attaining initial fitness objectives; it's about sustaining well-being in the long run.

SchoolCrusher

Improved Learning: SchoolCrusher empowers students with easy access to educational materials and interactive tools, fostering a deeper understanding of subjects. Quizzes and Assessments: Students can access a variety of quizzes and assessments tailored to their grade level and subject. These quizzes not only help in assessing your knowledge but also provide immediate feedback and explanations for incorrect answers. Homework Solvers: Stuck on a tricky math problem or a challenging physics equation? SchoolCrusher's homework solver can assist you step-by-step, guiding you to the correct solution and explaining the process along the way. Essay Writers: Writing essays can be a daunting task, but SchoolCrusher's essay writer feature makes it easier. Students can input their essay prompts, and the chatbot generates well-structured essays, complete with citations and references, saving valuable time and reducing writer's block. Subject-Specific Support: SchoolCrusher specializes in a wide range of subjects, from mathematics and science to literature and history. It offers subject-specific insights, study tips, and additional resources to enhance your understanding. Study Plans: The chatbot can help students create customized study plans based on their goals and schedules. It takes into account upcoming exams and assignments to ensure efficient time management. Language Support: SchoolCrusher is multilingual, providing support in various languages to cater to a diverse user base. Personalized Learning: With customized study plans and subject-specific support, SchoolCrusher tailors its assistance to individual needs. Teacher Efficiency: Teachers can streamline their lesson planning and assessment processes, allowing them to focus more on teaching. Accessibility: The chatbot's 24/7 availability ensures that learning and teaching resources are always within reach.

Stock Market Sentiment Analysis

Here's a breakdown of the key components and objectives of our project: 1. **Historical Data Analysis**: our project starts by collecting and analyzing historical stock data, which includes information such as stock prices and trading volumes. 1. **Price Movement Analysis**: One aspect of your analysis involves studying price movements. This includes examining the changes in stock prices over time to identify significant increases or decreases. By analyzing price movements, you can identify dates where the market experienced significant price fluctuations. 1. **Volume Movement Analysis**: Another important aspect of your analysis is studying volume movements. Trading volume refers to the number of shares traded during a specific time period. By analyzing volume movements, you can identify dates where there was a notable increase or decrease in trading activity. Unusual volume spikes can indicate significant market moves. 1. **Event Identification**: Once you have identified dates with significant price and volume movements, your project aims to associate those dates with specific events or news that occurred. This could involve correlating market moves with company earnings releases, economic announcements, geopolitical events, or other relevant factors. By identifying events associated with market moves, you can provide context and explanations for the observed trends. 1. **Future Expectations**: In addition to analyzing historical data, our project aims to provide insights into future market behavior. By giving you the

Autonomo

Live Streamers lack of time and opportunity for responding to every message from their fans during the live stream. And they find it hard to remember who their fans are and their last interaction with them, which makes it a weird of a relationship between the streamer and their fans. In addition to that potential sponsors can’t decide easily which streamer’s community is the right one to promote their product/service. Here's where Autonomo comes with the solution, Autonomo is a multifunctional chatbot that enhances the relationship between fans and live Streamers/Broadcasters, analyzes the community formed by fans and classifies them into a category. The Live streamer is then able to put the category its community classifies under in a marketplace where potential sponsors would search for the right one to promote their product/service. The more chat messages collected from a channel, the better it is for Autonomo to know what the community is interested in and to even answer community members with relevant answers when prompted. Autonomo leverages the advantage of vector Databases to assist LLMs and thus enhance its performance and its ability to remember.