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as 06-21-2024 4:00pm EST

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Consumer Discretionary

Auto Parts:O.E.M.

Nasdaq

SES AI Corp is a pre-commercialization stage company engaged in the development and initial production of high-performance Lithium-Metal (Li-Metal) rechargeable battery technologies for electric vehicles (EVs), urban air mobility (UAM), which encompasses electric vehicle take-off and landing (eVTOL), and other applications. The company is an integrated Li-Metal battery manufacturer with capabilities in material, cell, module, AI-powered safety algorithms, and recycling.

More About Our SES ML Model...

What kind of parameters do you use to train SES stocks ML model?

To train our stocks SES ML model, we use historical data with over 25 parameters, including volume indicators, volatility indicators, momentum indicators, trend indicators, and other metrics.

How often do you update SES ML model?

We update our ML model either weekly or biweekly, depending on the market capitalization of the stocks, using TensorFlow, typically over the weekend.

Why is the accuracy of your SES model low?

Unfortunately, our current data provider offers limited historical data, which impacts the accuracy of our ML model. However, as we continue to gather more data over time and add more indicators, we expect the accuracy of our model to improve.

How can I provide and share more data with you to increase your ML model accuracy?

We would greatly appreciate your contribution. Please send an email to [email protected]

Do you offer an ML model for shorter time periods, such as 5 minutes or 15 minutes?

Yes, we offer it for strategy purposes only, with intervals: 1 minute, 2 minutes, 5 minutes, 15 minutes, and 30 minutes etc.

Can I rely on your ML model to make financial decisions regarding buying or selling stocks, or is it only intended for learning purposes?

Our ML model is primarily designed for educational purposes and is not intended to provide financial advice. We strongly recommend consulting with a financial advisor before making any buying or selling decisions.

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