ESG-AI-investment-by-streamlit
WallStreetBets_BigDataAnalysis
| ESG-AI-investment-by-streamlit | WallStreetBets_BigDataAnalysis | |
|---|---|---|
| 2 | 1 | |
| 22 | 165 | |
| - | - | |
| 8.8 | 0.0 | |
| about 1 month ago | 9 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ESG-AI-investment-by-streamlit
-
[P] ESG scoring with Node2Vec and web-site with streamlit!
Github: https://github.com/monouns/ESG-AI-investment-by-streamlit
- [P] Let me share my Proj: ESG AI with webpage Streamlit
WallStreetBets_BigDataAnalysis
What are some alternatives?
ESG_AI
amazon-denseclus - Clustering for mixed-type data
pyspark_nlp_workshop - Instructions and code for the workshop "From Big Data to NLP Insights: Unlocking the Power of PySpark and Spark NLP"
project - Predict how many points an European football team will end the season with, according to the characteristics of its players. Project for the Big Data Computing course at Sapienza University of Rome (2021-22)
dracula - a brief analysis to the most common words in Dracula, by Bram Stoker
reddit-streaming - streaming eight subreddits from reddit api using kafka producer & spark structured streaming.
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
NLU-engine-prototype-benchmarks - Demo and benchmarks for building an NLU engine similar to those in voice assistants. Several intent classifiers are implemented and benchmarked. Conditional Random Fields (CRFs) are used for entity extraction.