bulbea
n4m-sentiment
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bulbea | n4m-sentiment | |
---|---|---|
97 | 1 | |
1,969 | 10 | |
- | - | |
0.0 | 0.0 | |
over 3 years ago | almost 3 years ago | |
Python | Max | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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bulbea
n4m-sentiment
-
n4m-sentiment : sentiment analysis for MaxMSP
Download it for free here: https://github.com/lysdexic-audio/n4m-sentiment
What are some alternatives?
mlfinlab - MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
afinn - AFINN sentiment analysis in Python
stock-prediction-deep-neural-learning - Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
n4m-handpose - Wraps MediaPipe HandPose inside electron and serves the detected parts via MaxAPI.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
awesome-sentiment-analysis - Repository with all what is necessary for sentiment analysis and related areas
Deep_Learning_Machine_Learning_Stock - Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
tuneta - Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
Deep-Learning-Machine-Learning-Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders. [Moved to: https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock]