Best AI tools for< Nba Analyst >

Leans.AI is an AI-powered sports prediction algorithm that provides free sports picks and predictions for NFL, NBA, CBB, NHL, MLB, and CFB games. It uses AI technology to analyze thousands of data points on each game, calculate cover probabilities, assign units to picks, and release top picks daily. The application aims to help users make informed betting decisions based on data-driven insights and improve their chances of winning against the spread. Leans.AI is known for its transparency, historical performance metrics, and continuous improvement through machine learning techniques.

Mysports AI is a cutting-edge AI sports prediction tool that leverages deep learning technology to provide valuable betting insights and profitable bets. The platform offers users the opportunity to enhance the value of their betting experience by utilizing AI-generated models and strategies. With a focus on long-term profitability and high win rates, Mysports AI aims to revolutionize the sports betting industry by offering a user-friendly interface and a wide range of sportsbooks to choose from.

XaslarBet is an AI betting tips platform that provides advanced trained models for NBA player props and football picks. The platform offers free AI sports tools using predictive analytics and machine learning algorithms to enhance the betting experience. XaslarBet focuses on player performances and historical data to deliver accurate picks across various sports markets, including basketball, baseball, and cricket. The platform aims to revolutionize the betting landscape by offering real-time AI sports predictions for both newcomers and seasoned bettors.

Rithmm is an AI sports betting application that offers custom models for AI picks and props. It provides AI sports picks for various sports leagues like NFL, NBA, NCAAF, NCAAB, Golf, and WNBA. Users can access player props and game picks backed by AI predictive models to make informed betting decisions. Rithmm simplifies complex data into user-friendly insights, making it suitable for both seasoned bettors and beginners. The application aims to empower users to make smarter bets effortlessly with the use of AI technology.

This tool is a machine learning AI used to predict the winners and under/overs of NBA games. It takes all team data from the 2007-08 season to the current season, matched with odds of those games, and uses a neural network to predict winning bets for today's games. The tool achieves ~69% accuracy on money lines and ~55% on under/overs. It outputs expected value for teams' money lines to provide better insight and the fraction of your bankroll to bet based on the Kelly Criterion. A popular, less risky approach is to bet 50% of the stake recommended by the Kelly Criterion.

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured evaluations (covering language, code, embedding use cases), perform root cause analysis on failure cases and give insights on how to resolve them.

ML Contests is a platform that provides a sortable list of public machine learning/data science/AI contests, viewable on mlcontests.com. Users can submit pull requests for any changes or additions to the competitions list by editing the competitions.json file on the GitHub repository. The platform requires mandatory fields such as competition name, URL, type of ML, deadline for submissions, prize information, platform running the competition, and sponsorship details. Optional fields include conference affiliation, conference year, competition launch date, registration deadline, additional URLs, and tags relevant to the challenge type. The platform is transitioning towards assigning multiple tags to competitions for better categorization and searchability.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

This repo contains a comprehensive paper list of **Model Quantization** for efficient deep learning on AI conferences/journals/arXiv. As a highlight, we categorize the papers in terms of model structures and application scenarios, and label the quantization methods with keywords.

Fast, efficient NBA analyst for game predictions.

Chat about NBA stats with Sheed!!! — (Source/credit: @hi_im_danny / balldontlie.io)

Global basketball expert with a focus on EuroLeague and NBA. In-depth analyses and predictions.

Comprehensive NBA stats analysis with sports flair.

Get information about pro teams (NHL, NBA, NFL, MLB) teams by calling the ndricks Software Sports API.

All the Lakers gossip

A bot that vents frustration about the New York Knicks.