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

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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.

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.

RushDownAI

Introducing the cutting-edge Virtual Manager platform tailored for College Athletes, where athletes can seamlessly connect with potential brands through AI-driven conversations. This innovative site will revolutionize brand partnerships by enabling athletes to engage in natural and personalized dialogues with prospective sponsors. The Virtual Manager will utilize a sophisticated AI algorithm to craft compelling scripts that integrate the brand's projects with the athlete's unique profile. Drawing from a comprehensive database of the athlete's past games and achievements, the AI-powered script generator will seamlessly weave together a synopsis of key moments and performance highlights. By factoring in the athlete's playing style, personality traits, and values, the script will resonate authentically, ensuring a genuine alignment between the athlete and the brand. This platform transcends the traditional means of sponsorship negotiations, fostering deeper connections by showcasing the athlete's journey and achievements in a relatable manner. The Virtual Manager site for College Athletes offers a streamlined interface where athletes can review, customize, and refine the generated scripts. The AI system adapts to feedback, continually improving its ability to capture the athlete's essence and effectively communicate with brands. Brands, on the other hand, gain insights into the athlete's on-field prowess, character, and fan following, enabling them to make informed sponsorship decisions. In essence, the Virtual Manager site for College Athletes stands at the crossroads of technology, sports, and business, redefining how athlete-brand collaborations are forged. By merging AI-generated scripts, past game synopses, and individual personas, this platform ensures a dynamic and fruitful partnership between college athletes and prospective brands, enhancing the sports sponsorship landscape in an unprecedented way.

GitScale

GitScale" is a groundbreaking project that revolutionizes the field of product management. This innovative platform leverages the power of automation to generate dynamic Kanban boards, seamlessly integrating data from various sources such as CRMs, Crashalytics, Ticketing Software, Product Vision Calls, and Usage Analytics. By automating the creation of Kanbans, GitScale empowers teams to concentrate on the most critical aspect of their work – solving issues and driving product development forward. GitScale currently interfaces with HubSpot, Firebase Analytics, Zendesk, and DataDog to construct and maintain a responsive product roadmap, eradicating concerns about outdated tasks or missed scrum meetings. The project's challenges include the implementation of n-shot learning to craft semi-structured responses from OpenAI output and effectively deciphering domain knowledge encompassing company products, staff details, and customer profiles, all within a limited contextual space. Furthermore, GitScale addresses the intricate task of consolidating multiple client requirements for priority assignment while ensuring that they are appropriately segmented into individual tasks. With GitScale, product management becomes a streamlined and efficient process, ultimately enhancing productivity and outcomes.

MindfulAI - AI Agents for Mental and Eye Health

Our idea is to use AI, ML and open source technologies to revolutionize the healthcare fields - specifically Mental Wellness and Eye Care using Autonomous AI Agents. These Autonomous AI Agents are using SuperAGI and deployed on AWS. We have given the choice to users on our landing page to use Eye Health or AI Therapist for their purposes. The Eye Health uses Eye Care AI Agent to track blinks of users and let them know how their eyes are and what is the blink status of their eyes using real time live webcam feed. This will help to notify users and recommend them best strategies for eye care and early stage detection and prevention from diseases like Dry Eyes Disorders. We have the AI Therapist that uses Mental Wellness AI Agent to track the moods of the user from a live webcam feed and the SuperAGI helps in replying to users based on the mood track what they should do in order to be in a good mood, this helps users to track real time their moods and get some suggestions from AI Therapist. People of all ages have the tendency to have long working hours and exposures to screens and devices. These causes issues for eyes and also mental health gets affected due to such behaviors, mental wellness and some basic guidance as initial steps for healthcare can be provided by the AI Therapist and that can help users to track their mental moods, in future we can also allow them to have chatbots and have conversations with AI Therapist and Eye Care Agent. Eye Care Agent can help in tracking blinks and how good their eye health is and can suggest if their blink count per minute is less than 12, it can suggest the users to have some time off, do exercises, take a break, engage in healthy activities and take care of themselves. Screen time and usage of users can also be tracked and it can help to suggest users what steps to be taken in terms of productivity, creative and efficient parental controls, gaining better leverage on data using insights from AI & ML