Tf Quant Finance
High-performance TensorFlow library for quantitative finance.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Tf Quant Finance | 4,031 | | 2 | 6 months ago | 30 | August 19, 2022 | 36 | apache-2.0 | Python | |
| High-performance TensorFlow library for quantitative finance. | ||||||||||
| Multi Class Text Classification Cnn | 388 | 6 years ago | 24 | apache-2.0 | Python | |||||
| Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow. | ||||||||||
| Watch Me Build A Finance Startup | 156 | 5 years ago | mit | Java | ||||||
| This is the code for "Watch Me Build a Finance Startup" by Siraj Raval on Youtube | ||||||||||
| Machine Learning And Reinforcement Learning In Finance | 135 | 4 years ago | 4 | Jupyter Notebook | ||||||
| Machine Learning and Reinforcement Learning in Finance New York University Tandon School of Engineering | ||||||||||
| Finbert | 101 | 4 years ago | 2 | C++ | ||||||
| BERT for Finance : UC Berkeley MIDS w266 Final Project | ||||||||||
| Speculator | 90 | 1 | 6 years ago | 11 | December 19, 2017 | mit | Python | |||
| API for predicting the next Bitcoin and Ethereum with machine learning and technical analysis | ||||||||||
| Market_risk_gan_tensorflow | 77 | a year ago | 19 | apache-2.0 | Python | |||||
| Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management using TensorFlow. | ||||||||||
| Stock2vec | 26 | 7 years ago | Jupyter Notebook | |||||||
| Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history | ||||||||||
| Stocky | 25 | 7 years ago | Python | |||||||
| Machine Learning Stock Trading Risk Analysis (Spring 2017) | ||||||||||
| Appendices | 25 | 2 years ago | ||||||||
| Complement the article 'Differential Machine Learning' (Huge & Savine, 2020), including mathematical proofs and important implementation details for production | ||||||||||
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