Browse applications built on Reinforcement Learning technology. Explore PoC and MVP applications created by our community and discover innovative use cases for Reinforcement Learning technology.
The Bloopa cat symbolizes inclusivity, adaptability, and positivity! 🐱💖 Representing our mission to build a next-generation Assistive tech that embodies the spirit of creating accessible, empowering technology for all, fostering inclusivity globally🌍
An AI-powered Islamic assistant that uses advanced models and a RAG pipeline to provide Quranic verses in Arabic, along with translations, explanations, and references, ensuring accurate and contextually relevant responses to users' queries.
Primary Goal: Develop a platform to assist businesses in enhancing their online reviews. Secondary Goals: Provide tools for businesses to analyze and respond to customer feedback. Implement strategies to encourage positive reviews from customers
Our project provides multilingual video dubbing with emotional nuances, synchronized subtitles, lip-sync technology, and video supers. It also generates concise text and video summaries, ensuring accessible and engaging content for a global audience.
Viable Trends* per day on day occurrence across a few sectors.
Languify revolutionizes language learning with personalized, immersive experiences powered by LLM technology, offering tailored paths for each user's proficiency level and learning style.
Send Personalized Motivational Messages to Coaching Clients!
ML Fast Lane with GPU Power. AI-driven, GPU-accelerated ML platform. Seamlessly build, train, and deploy models with blazing speed and intelligence.
HyperTarget, a groundbreaking AI plugin for WordPress, embeds personalized affiliate content directly into blog posts in real time. Tailored to individual reader's interests, it amplifies engagement and revenue like never before.
Smart AI Text Editor that can generate content based on the written data & also: Fix grammar, Paraphrase it, and Improve your Text. Can also summarize links as well.
Your Appointment Setter with Artificial Intelligence scheduling meetings and calls on autopilot
A trading agent AI is an artificial intelligence system that uses computational intelligence methods such as machine learning and deep reinforcement learning to automatically discover, implement, and fine-tune strategies for autonomous adaptive automated.
LangX is an AI agent that aims to make learning languages easy with AI technology like openai and lancghain
GPTUBE is aimed to convert youtube videos to seo blog posts in the blink of an eye we have made a system that converts youtube videos into seo blog posts seamlessly with a very good user experience
Utilizing AutoGPT and LangChain, we use linux based network security tools for malware and intrusion prevention. AI to keep your network secure and up-to-date.
Revolutionizing the Automotive World with AI-Powered 3D Models.
Daila is a personalized learning app that utilizes the power of GPT-3.5 and AWS services to provide a unique and tailored learning experience for students or pretty much everyone who wants to learn.
Supercharge your business operation by using AI technology.
Hyperbot 🤖 assists with coding queries, generates art, provides real-time updates on current affairs and weather forecasts, composes tweets, LinkedIn posts, emails, and plays music of your choice or displays your favorite YouTube video.
An artificial intelligence podcast that is written by ChatGPT, GPT-3.5, Open-AI davinci, and human assistance. The art is generated by Stable Diffusion, Open Journey, and Dall-E 2. It is read by Natural Readers text-to-speech and Lifelike Speech Synthesis
Your personalized chatbot companion, trained exclusively on your chosen content, with secure and private access – tailored conversations made just for you!
RL Introductory Hackathon for envs Cartpole, Walker , Lunar Lander
3 environments, everything is good
Using the stable_baselines3 library, we tried to solve the problems proposed in the challenge. We used a Proximal Policy Optimization (PPO) Model. The Policy we used is a standard MLP. We tried to change the number of iteration to achieve a better performance.
We have completed 2 challenges. The first one (cartpole) was completed using our own code, we implemented Deep Q Learning. For the second one (Lunar Lander) we used stable_baseline library.
Applied reinforcement learning for agent to play these 3 games: Cartpole, LunarLander, BiPedal Walker. We used the basic model of Environment -> State -> Agent -> Action to train our agent. We reward the agent for achieving an outcome that we want, while penalizing the agent for doing otherwise. After many iterations, our agents learns to clear the games.
Used A2C and DQN for Lunar Lander DQN for Cartpole TQC for Bipedal Walker