Best AI tools for< predict diamond prices >

Diatech AI is a company that provides advanced AI solutions for the diamond industry. Their services include demand-supply analytics, price analytics, customer behavior analytics, market prediction, and more. They also have a marketplace where suppliers and buyers can trade diamonds, and a platform for tracking the provenance of diamonds and substantiating claims about ethical practices. Additionally, they offer white-labeled storefronts and marketplaces, and tools for tracking and analyzing customer behavior.

The Predict API is a powerful tool that allows you to forecast your data with simplicity and accuracy. It uses the latest advancements in stochastic modeling and machine learning to provide you with reliable projections. The API is easy to use and can be integrated with any application. It is also highly scalable, so you can use it to forecast large datasets. With the Predict API, you can gain valuable insights into your data and make better decisions.

Numerai is a data science tournament platform where users can compete to build models that predict the stock market. The platform provides users with clean and regularized hedge fund quality data, and users can build models using Python or R scripts. Numerai also has a cryptocurrency, NMR, which users can stake on their models to earn rewards.

Neurons is a platform that uses AI to predict consumer responses and behavior. It offers a variety of solutions for businesses, including marketing agencies, designers, and e-commerce companies. Neurons' AI-powered tools can help businesses optimize their marketing campaigns, improve their product design, and better understand their customers.

AutoPredict is the first app that uses artificial intelligence to predict how long a car will last. By analyzing over 100 million data points, AutoPredict gives an accurate estimate of your car's life.

Focia is a content intelligence platform that helps you predict engagement, rank and compare your content ideas, get feedback, and forecast engagement metrics. With Focia, you can maximize your engagement and create content that resonates with your audience.

Simpleem is an Artificial Emotional Intelligence (AEI) tool that helps users uncover intentions, predict success, and leverage behavior for successful interactions. By measuring all interactions and correlating them with concrete outcomes, Simpleem provides insights into verbal, para-verbal, and non-verbal cues to enhance customer relationships, track customer rapport, and assess team performance. The tool aims to identify win/lose patterns in behavior, guide users on boosting performance, and prevent burnout by promptly identifying red flags. Simpleem uses proprietary AI models to analyze real-world data and translate behavioral insights into concrete business metrics, achieving a high accuracy rate of 94% in success prediction.

AI Baby Generator is a website that uses artificial intelligence to generate realistic photos of your future baby. Simply upload a photo of yourself and your partner, and the AI will create a photo of your future child. You can also choose to upload a photo of a celebrity as your partner, or simply describe your physical features on the order form. The AI will then generate a baby based on these descriptions. AI Baby Generator also offers a 7-page personality report that includes your future baby's sign, love language, personal quirk, special talent, relationship with future child, Myers-Briggs personality type, personality traits, likes, and hobbies.

CreatorML is an AI-powered platform designed to help YouTube creators optimize their content and grow their channels. Using machine learning, CreatorML's tools can predict how well a video will perform before it's even published, suggest title and thumbnail ideas, and provide insights into what's trending on YouTube. CreatorML is designed for YouTube creators of all levels, from beginners to experienced professionals. It offers a variety of subscription plans to fit every budget and need.

Keepme is an AI-powered platform designed for gyms to boost sales, predict and prevent attrition, and enhance member retention. It offers features such as Keepme Score™ for predicting attrition, smart lead scoring, gym tours & trials scheduler, NPS surveys, smart campaigns & automations, smart content production, and WhatsApp integration. The platform provides personalized training and world-class support through Keepme Academy and customer success team. Keepme is trusted by over 450 fitness clubs globally and offers valuable AI resources to empower users with knowledge.

AI Sports Betting Predictions is a website that provides AI-powered predictions for football matches. The website offers a range of predictions, including match outcomes, goal scorers, and player assists. AI Sports Betting Predictions also provides live scores and odds comparison from a large number of bookmakers. The website's mission is to bring high-quality forecasts at a low cost to sports fans across the globe.

NovaResp cMAP™ is an AI-powered platform software designed to improve adherence to Continuous Positive Airway Pressure (CPAP) therapy for sleep apnea patients. It utilizes artificial intelligence and machine learning to predict and prevent apnea episodes during therapy, delivering personalized treatment at more comfortable air pressure levels. The application aims to enhance patient quality of life, increase sales for device manufacturers, and reduce labor costs for DMEs. NovaResp cMAP™ is compatible with all major PAP machines and is a revolutionary solution in the treatment of Obstructive Sleep Apnea (OSA).

CaseYak is an AI-powered case calculator that helps personal injury attorneys estimate the value of their clients' claims. The calculator uses machine learning to analyze data from over 10 years of jury verdicts to provide an objective and data-driven prediction of case value. CaseYak's mission is to provide more information to people who are considering seeking legal recourse after being injured in a car accident. CaseYak's calculator is easy to use and takes less than 5 minutes to complete. Simply provide information about your accident, your injuries and symptoms, your medical expenses, and your lost wages, and CaseYak's machine learning model will give you an estimate of what kind of verdict a jury would return in your case. Of course, this is for general informational purposes only and certain assumptions are made, so be sure to read the terms and conditions and consult with a personal injury attorney.

SupportLogic is a cloud-based support experience management platform that uses AI to help businesses improve their customer support operations. The platform provides a range of features, including sentiment analysis, case routing, and quality monitoring, that can help businesses to identify and resolve customer issues quickly and efficiently. SupportLogic also offers a number of integrations with popular CRM and ticketing systems, making it easy to implement and use.

SupportLogic is a Support Experience Management Platform that uses AI to help businesses improve their customer support operations. It offers a range of features, including sentiment analysis, backlog management, intelligent case routing, proactive alerts, swarming and collaboration, account health management, customer support analytics, text analytics, SLA/SLO management, quality monitoring and coaching, agent productivity, and translation. SupportLogic integrates with existing ticketing systems and apps, and can be implemented within 45 days.

Ogoodo is a Kanban tool that helps teams to visualize their workflow, track their progress, and improve their productivity. It offers a variety of features to support the Kanban framework, including a board view, time tracking, timeline prediction, and analytics. Ogoodo is designed to be easy to use and can be customized to fit the needs of any team.

Nextatlas Generate is a generative trend forecasting service that uses advanced natural language processing and machine learning algorithms to analyze vast amounts of data and predict future trends in a wide range of industries and markets. It is powered by GPT-4 and the Nextatlas engine, which analyzes data from over 300k early adopters on social media to identify emerging trends. Generate can create high-quality, human-like content, such as blog articles, social media posts, and trend reports, tailored to specific industries and topics. It also features a Casefinder, an AI-driven matchmaker for business cases, and visualization tools for effective data interpretation.

TripBudget is an AI-powered travel cost prediction tool that helps users plan and budget for their trips. It uses machine learning algorithms to analyze historical travel data and provide accurate estimates of travel expenses. TripBudget is designed to make travel planning easier and more affordable for everyone.

LatenceTech is a tech startup that helps businesses to visualize and analyze their network latency issues in real time. We provide real-time monitoring, prediction, and in-depth analysis of your network using our AI software. Our end-to-end real-time observability ensures high-quality network and low latency.

Predis.ai is an AI-powered application that offers predictive analytics solutions for businesses. It leverages advanced machine learning algorithms to analyze data and provide valuable insights to help companies make informed decisions. With a user-friendly interface, Predis.ai simplifies the process of data analysis and forecasting, making it accessible to users with varying levels of technical expertise. The application is designed to assist organizations in optimizing their operations, improving efficiency, and identifying trends to stay ahead in a competitive market.

This repository is designed to inject backdoors into Language Model Models (LLMs) for code. The injected backdoors serve as timestamps for the training dataset of the LLMs. The code is randomly generated and includes watermark backdoors to show specific behaviors. A script automatically updates the repository with a new backdoor every month. Validating the existence of the backdoor can infer when the training dataset was collected. The backdoors are constructed in a specific format, and verifying them may require multiple tries. The repository keeps a record of backdoors injected along with associated dates.

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.

FootBallPrediction (FBP) is a software project that utilizes big data and machine learning to predict the outcome of football matches based on odds from gambling companies. The software has achieved an accuracy rate of over 80% in predicting match results. The current version, 22.0, successfully predicted eight out of nine matches from major football leagues. The project has a community of over 60 members who benefit from the predicted results. The author is seeking collaboration to further enhance the project and welcomes interested individuals to join. AI-FBP is a subscription service that provides daily football game predictions.

This repo contains official implementations of **Coach AI Badminton Project** from Advanced Database System Laboratory, National Yang Ming Chiao Tung University supervised by Prof. Wen-Chih Peng. The high-level concepts of each project are as follows: 1. Visualization Platform published at _Physical Education Journal 2020_ aims to construct a platform that can be used to illustrate the data from matches. 2. Shot Influence and Extension Work published at _ICDM-21_ and _ACM TIST 2022_ , respectively introduce a framework with a shot encoder, a pattern extractor, and a rally encoder to capture long short-term dependencies for evaluating players' performance of each shot. 3. Stroke Forecasting published at _AAAI-22_ proposes the first stroke forecasting task to predict the future strokes of both players based on the given strokes by ShuttleNet, a position-aware fusion of rally progress and player styles framework. 4. Strategic Environment published at _AAAI-23 Student Abstract_ designs a safe and reproducible badminton environment for turn-based sports, which simulates rallies with different angles of view and designs the states, actions, and training procedures. 5. Movement Forecasting published at _AAAI-23_ proposes the first movement forecasting task, which contains not only the goal of stroke forecasting but also the movement of players, by DyMF, a novel dynamic graphs and hierarchical fusion model based on the proposed player movements (PM) graphs. 6. CoachAI-Challenge-IJCAI2023 is a badminton challenge (CC4) hosted at _IJCAI-23_. Please find the website for more details. 7. ShuttleSet published at _KDD-23_ is the largest badminton singles dataset with stroke-level records. - An extension dataset ShuttleSet22 published at _IJCAI-24 Demo & IJCAI-23 IT4PSS Workshop_ is also released. 8. CoachAI Badminton Environment published at _AAAI-24 Student Abstract and Demo, DSAI4Sports @ KDD 2023_ is a reinforcement learning (RL) environment tailored for AI-driven sports analytics, offering: i) Realistic opponent simulation for RL training; ii) Visualizations for evaluation; and iii) Performance benchmarks for assessing agent capabilities.

This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

Pai-Megatron-Patch is a deep learning training toolkit built for developers to train and predict LLMs & VLMs by using Megatron framework easily. With the continuous development of LLMs, the model structure and scale are rapidly evolving. Although these models can be conveniently manufactured using Transformers or DeepSpeed training framework, the training efficiency is comparably low. This phenomenon becomes even severer when the model scale exceeds 10 billion. The primary objective of Pai-Megatron-Patch is to effectively utilize the computational power of GPUs for LLM. This tool allows convenient training of commonly used LLM with all the accelerating techniques provided by Megatron-LM.

CleanStream is an OBS plugin that utilizes AI to clean live audio streams by removing unwanted words and utterances, such as 'uh's and 'um's, and configurable words like profanity. It uses a neural network (OpenAI Whisper) in real-time to predict speech and eliminate unwanted words. The plugin is still experimental and not recommended for live production use, but it is functional for testing purposes. Users can adjust settings and configure the plugin to enhance audio quality during live streams.

Nixtla is a production-ready generative pretrained transformer for time series forecasting and anomaly detection. It can accurately predict various domains such as retail, electricity, finance, and IoT with just a few lines of code. TimeGPT introduces a paradigm shift with its standout performance, efficiency, and simplicity, making it accessible even to users with minimal coding experience. The model is based on self-attention and is independently trained on a vast time series dataset to minimize forecasting error. It offers features like zero-shot inference, fine-tuning, API access, adding exogenous variables, multiple series forecasting, custom loss function, cross-validation, prediction intervals, and handling irregular timestamps.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

skpro is a library for supervised probabilistic prediction in python. It provides `scikit-learn`-like, `scikit-base` compatible interfaces to: * tabular **supervised regressors for probabilistic prediction** \- interval, quantile and distribution predictions * tabular **probabilistic time-to-event and survival prediction** \- instance-individual survival distributions * **metrics to evaluate probabilistic predictions** , e.g., pinball loss, empirical coverage, CRPS, survival losses * **reductions** to turn `scikit-learn` regressors into probabilistic `skpro` regressors, such as bootstrap or conformal * building **pipelines and composite models** , including tuning via probabilistic performance metrics * symbolic **probability distributions** with value domain of `pandas.DataFrame`-s and `pandas`-like interface

Skyrim is a weather forecasting tool that enables users to run large weather models using consumer-grade GPUs. It provides access to state-of-the-art foundational weather models through a well-maintained infrastructure. Users can forecast weather conditions, such as wind speed and direction, by running simulations on their own GPUs or using modal volume or cloud services like s3 buckets. Skyrim supports various large weather models like Graphcast, Pangu, Fourcastnet, and DLWP, with plans for future enhancements like ensemble prediction and model quantization.

AlphaFold3 is an implementation of the Alpha Fold 3 model in PyTorch for accurate structure prediction of biomolecular interactions. It includes modules for genetic diffusion and full model examples for forward pass computations. The tool allows users to generate random pair and single representations, operate on atomic coordinates, and perform structure predictions based on input tensors. The implementation also provides functionalities for training and evaluating the model.

Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as synthetic data generated using Gaussian processes.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

Forust is a lightweight package for building gradient boosted decision tree ensembles. The algorithm code is written in Rust with a Python wrapper. It implements the same algorithm as XGBoost and provides nearly identical results. The package was developed to better understand XGBoost, as a fun project in Rust, and to experiment with adding new features to the algorithm in a simpler codebase. Forust allows training gradient boosted decision tree ensembles with multiple objective functions, predicting on datasets, inspecting model structures, calculating feature importance, and saving/loading trained boosters.

The NZT Poker AI Bot is an advanced tool designed to revolutionize poker gameplay by providing comprehensive features to dominate 17 rooms with the Cash Fish Monitor. It offers detailed analysis of opponents' VPIP and PFR, extensive hand history database, opponent exploitation techniques, data-driven intelligence, player profiles, advanced neural network technology, expert training, continuous refinement, and cutting-edge algorithms for maximizing poker profits. Created by a team of poker experts, this AI tool continuously adapts to the latest poker strategies and utilizes state-of-the-art technology to enhance decision-making prowess.

Termax is an LLM agent in your terminal that converts natural language to commands. It is featured by: - Personalized Experience: Optimize the command generation with RAG. - Various LLMs Support: OpenAI GPT, Anthropic Claude, Google Gemini, Mistral AI, and more. - Shell Extensions: Plugin with popular shells like `zsh`, `bash` and `fish`. - Cross Platform: Able to run on Windows, macOS, and Linux.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

A curated list of data science & AI guided projects to start building your portfolio. The repository contains guided projects covering various topics such as large language models, time series analysis, computer vision, natural language processing (NLP), and data science. Each project provides detailed instructions on how to implement specific tasks using different tools and technologies.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

I predict DAU based on growth and retention.

Predict the future, opine on politics and controversial topics, and have GPT assess what is "true"

I predict future stock market prices. AI analyst. Your trading analysis assistant. Press H to bring up prompt hot key menu. Not financial advice.

Analyze Financial Statements step by step to Predict Earnings Direction

Predict fashion trends

AI expert in analyzing historical patterns to predict future events

Does Pool Performance of Elite Triathletes Predict Open-Water Performance?

A moot competition companion. & Trial Prep companion . Test and improve arguments- predict your opponent's reaction.

Personalized, analytical sports prediction AI.

あなたの顔を予想します

Predicts gender for first names using data

Horoscopes--八字算命术预测你的健康、婚姻、事业、财富...

Analyzes and predicts the SSE 500 Index.

1620年代の主要な歴史的出来事を分析し未来の予測に役立てる。

A question ? Ask me for a prediction ... ( /help for help )

MMA Expert & Trainer

Advanced AI for real-time predictive analysis using machine learning.

Advanced NFL and parlay predictor with comprehensive analysis

Fast, efficient NBA analyst for game predictions.

Advanced predictive analysis tool