CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

Official codebase for I-JEPA, the Image-based Joint-Embedding Predictive Architecture. First outlined in the CVPR paper, "Self-supervised learning from images with a joint-embedding predictive architecture."

Convolutional Neural Networks to predict the aesthetic and technical quality of images.

The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

Pytorch implementation of Transfusion, "Predict the Next Token and Diffuse Images with One Multi-Modal Model", from MetaAI

Cosmos-Predict2.5, the latest version of the Cosmos World Foundation Models (WFMs) family, specialized for simulating and predicting the future state of the world in the form of video.

基于ET框架致敬LOL的Moba游戏，提供完整的状态帧同步框架，包含预测回滚逻辑，基于双端行为树的技能系统，更多精彩等你发现！Based on the ET framework, we pay tribute to LOL's Moba game, providing a complete state frame synchronization framework, including predictive rollback logic, a skill system based on double-ended behavior trees, and more exciting things waiting for you to discover!

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.

Mask3D predicts accurate 3D semantic instances achieving state-of-the-art on ScanNet, ScanNet200, S3DIS and STPLS3D.

Python implementation of MPPI (Model Predictive Path-Integral) controller to understand the basic idea. Mandatory dependencies are numpy and matplotlib only.

DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.

A linear estimator on top of clip to predict the aesthetic quality of pictures

The mpc_local_planner package implements a plugin to the base_local_planner of the 2D navigation stack. It provides a generic and versatile model predictive control implementation with minimum-time and quadratic-form receding-horizon configurations.

Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.

You can easily calculate FVD, PSNR, SSIM, LPIPS for evaluating the quality of generated or predicted videos.

APCA (Accessible Perceptual Contrast Algorithm) is a new method for predicting contrast for use in emerging web standards (WCAG 3) for determining readability contrast. APCA is derived form the SAPC (S-LUV Advanced Predictive Color) which is an accessibility-oriented color appearance model designed for self-illuminated displays.

The Ensembl Variant Effect Predictor predicts the functional effects of genomic variants

ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.

Code to reproduce the results in the FAIR research papers "Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples" https://arxiv.org/abs/2104.13963 and "Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations" https://arxiv.org/abs/2006.10803

基于CNN的旋转验证码解决方案✨Predict the rotation angle of given captcha picture through CNN

Track and predict the energy consumption and carbon footprint of training deep learning models.

Use Tensorflow to run CNN for predict stock movement. Hope to find out which pattern will follow the price rising.

A model predictive controller for quadruped robots based on the single rigid body model and written in python. Gradient-based (acados) or Sampling-based (jax)

My best submission to the Kaggle competition "Predicting a Biological Response", ranked 17th over 711 teams.

Poseidon is a python-based application that leverages software defined networks (SDN) to acquire and then feed network traffic to a number of machine learning techniques. The machine learning algorithms classify and predict the type of device.

This is a workshop on implementing model predictive control (MPC) and moving horizon estimation (MHE) on Matlab. The implementation is based on the Casadi Package which is used for numerical optimization. A non-holonomic mobile robot is used as a system for the implementation. The workshop video recording can be found here https://www.youtube.com/playlist?list=PLK8squHT_Uzej3UCUHjtOtm5X7pMFSgAL ... Casadi can be downloaded here https://web.casadi.org/

Jailbreak for ChatGPT: Predict the future, opine on politics and controversial topics, and assess what is true. May help us understand more about LLM Bias