Inspiration
Give advisors better insights to sustain the relationship between investors and customers.
What it does
Studies the market for stock prices and predicts the dependency of dividend rates on S&P500 for long term investments as well as using sentiment analysis on Twitter data.
How we built it
Reinforcement learning, deep learning, and neural networks using TensorFlow.
Challenges we ran into
Framing the right dataset for our analysis.
Accomplishments that we're proud of
Extremely accurate model which predicts on the S&P500, as well as unique finding of dependency numerous other market metrics to aid our application.
What we learned
We learned key factors that drive the investment sector, as well as leveraging machine learning models to make data-driven decisions to better help our advisors and clients.
What's next for SchwakAnalyzer
More personalized data to come up with better recommendation metric systems for advisors and clients.
Built With
- neuralnetworks
- pandas
- python
- reinforcement-learning
- scikit-learn
- tensorflow
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