artificialintelligence's People
artificialintelligence's Issues
Recommender Systems
Train a model to recommend items to users based on their past behavior.
Generative Models for Molecular Design
: Train generative models to design new molecules for a specific task, such as drug discovery.
Deep Reinforcement Learning for Robotics
Implement deep reinforcement learning algorithms to control a robot for tasks such as grasping or navigation.
Image Segmentation
Train a model to segment images into different regions, such as foreground and background.
Reinforcement Learning
Implement reinforcement learning algorithms such as Q-Learning or policy gradients to solve various control problems or play games.
Adversarial Training
Train a generative adversarial network (GAN) to generate new images.
Generating Text:
Train a model to generate text based on a prompt or a given context, using a GPT-2 type architecture.
Object Tracking
Use OpenCV's object tracking algorithms to track objects in a video stream
Convolutional Neural Networks (CNNs) for Medical Imaging
Train CNNs to perform medical imaging tasks, such as segmentation or classification of medical images.
Object Detection
Train a model to detect objects in an image using a framework such as YOLO or Faster RCNN
Time Series Forecasting
Train a model to forecast time series data, such as stock prices or weather data.
Recurrent Neural Networks (RNNs) for Time Series Analysis
Train RNNs to perform time series analysis tasks, such as anomaly detection or forecasting.
Variational Autoencoder (VAE)
Implement a VAE to generate new images based on a dataset, such as the CelebA dataset.
Graph Neural Networks (GNNs) for Social Network Analysis:
Train GNNs to perform graph classification, link prediction, or node classification on social network data.
Generative Adversarial Networks (GANs) with Attention Mechanisms
Implement attention mechanisms in GANs to improve image generation quality.
Transformers for Natural Language Processing (NLP)
Train transformers to perform NLP tasks such as named entity recognition, sentiment analysis, or machine translation.
Graph Neural Networks
Graph Neural Networks: Implement graph neural networks (GNNs) to perform graph classification or node classification tasks.
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. ๐๐๐
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google โค๏ธ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.