Explore live open-source projects and AI models.

:chart_with_upwards_trend: Machine Learning from the perspective of a Statistician using R

This project is a Python-based tool for analyzing carbon emissions and forecasting future trends. It uses synthetic data to simulate historical emissions and applies ARIMA (a time series model) and Linear Regression (a machine learning model) to predict future emissions

Poole, Mackworth & Goebel 1998, p. 1. Russell & Norvig 2003, p. 55. Definition of AI as the study of intelligent agents: Poole, Mackworth & Goebel (1998), which provides the version that is used in this article. These authors use the term "computational intelligence" as a synonym for artificial... Read more

Stock Market Trend Prediction using sentiment analysis Leveraging machine learning and sentiment analysis, we accurately forecast stock market trends. Our project combines advanced algorithms like BERT and Naïve Bayes with sentiment analysis from Twitter and other sources. By analyzing sentiment... Read more

We use advanced machine learning techniques to build models that correlate planet cycles and aspects (cosmic energy) with markets price action to forecast the daily trend direction. Join our discussions at Telegram:

Using TensorFlow machine learning and Twitter sentiment analysis to predict stock trends

:chart_with_upwards_trend: A live cryptocurrency historical trade data blotter. Download live historical trade data from any cryptoexchange, be it for machine learning, backtesting/visualizing trading strategies or for Quantopian/Zipline.

The Monthly Car Sales Analysis project uses data analytics, machine learning, and time series forecasting to track and predict car sales trends. It explores patterns by brand, model, region, and season, identifies consumer preferences, and generates insights that support marketing, inventory, and... Read more

Using machine learning to predict/forecast the future trend of stock prices.

Supplementary material for our paper "Compute Trends Across Three Eras of Machine Learning".