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ashishpatel26 / 500 AI Machine Learning Deep Learning Computer Vision NLP Projects With Code500 AI Machine learning Deep learning Computer vision NLP Projects with code
steven2358 / Awesome Generative AIA curated list of modern Generative Artificial Intelligence projects and services
KalyanM45 / AI Project GalleryThis Repository Contain All the Artificial Intelligence Projects such as Machine Learning, Deep Learning and Generative AI that I have done while understanding Advanced Techniques & Concepts.
py-why / EconMLALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
whoiskatrin / Sql TranslatorSQL Translator is a tool for converting natural language queries into SQL code using artificial intelligence. This project is 100% free and open source.
microsoft / MalmoProject Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment. --- For installation instructions, scroll down to *Getting Started* below, or visit the project page for more information:
wppconnect-team / WppconnectWPPConnect is an open source project developed by the JavaScript community with the aim of exporting functions from WhatsApp Web to the node, which can be used to support the creation of any interaction, such as customer service, media sending, intelligence recognition based on phrases artificial and many other things, use your imagination
qxresearch / Qxresearch Event 1Python hands on tutorial with 50+ Python Application (10 lines of code) By @xiaowuc2
felladrin / Awesome AI Web SearchList of software that allows searching the web with the assistance of AI: https://hf.co/spaces/felladrin/awesome-ai-web-search
CoderSJX / AI Resources CentralBringing together outstanding artificial intelligence (AI) open source projects from around the world.
steven2358 / Awesome Blockchain AIA curated list of Blockchain projects for Artificial Intelligence and Machine Learning
mdipietro09 / DataScience ArtificialIntelligence UtilsExamples of Data Science projects and Artificial Intelligence use-cases
hades217 / Awesome AIA curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project)
yanshengjia / Artificial IntelligenceAwesome Artificial Intelligence Projects
IBM / ClaiCommand Line Artificial Intelligence or CLAI is an open-sourced project from IBM Research aimed to bring the power of AI to the command line interface.
PacktPublishing / Python Artificial Intelligence Projects For BeginnersPython Artificial Intelligence Projects for Beginners, published by Packt
ponlponl123 / Prototype AIVTubera open-source Artificial Intelligence Virtual Youtuber (AI VTuber), (this project is deprecated)
pierpaolo28 / Artificial Intelligence ProjectsCollection of Artificial Intelligence projects.
WillKoehrsen / AI ProjectsArtificial Intelligence projects, documentation and code.
duemig / Stanford Project Predicting Stock Prices Using A LSTM NetworkStanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).
