26_Tao_Strategy market

Inspiration

We were always fascinated by stock market and this ideas stuck us a while ago.So we added market feature and a model trainer to improve upon the idea

What it does

It enables a user to create trading strategies which technical indicators and combine the power of ML/DL to leverage the profit.The platform also allows user to backtest their strategies for improving accuracies. We also provide market for user to sell and buy strategies and also train models to perform their specific tasks.

How we built it

We used a python framework called Streamlit and its component called Barfi. We used Barfi to build node graphs for making strategies and training models. We also implemented tensorflow to inculcate deep learning models. We used Deta base as a NoSQL database and Deta Cloud as a proxy for Binance Server.

Challenges we ran into

Incorporating buying and selling of strategies was a challenging task. In addition, model training was hard to configure and incorporate.

Accomplishments that we're proud of

This is our first hackathon and we are super proud of how much we accomplished although its not much. We learned a lot of new thing and were able to assess our strengths and weaknesses. We learned many new concepts and different ways to implent and view problems.

What we learned

We learned to work together and also learned to use and deploy web applications and also create node graphs for user cases.

What's next for Strat-Market

We will try to make a self sustaining app that allows a user to build their own AI model that automates the process of Stock marketing. Furthermore we would like to inculcate a social platform that allows the discussion between traders upon different aspects of Stock Marketing and Strategizing.

Built With

• barfi
• binanceapi
• deta-cloud
• python
• streamlit
• tensorflow