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as 11-20-2024 4:00pm EST

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Lam Research is one of the largest semiconductor wafer fabrication equipment manufacturers in the world. It specializes in deposition and etch, which entail the buildup of layers on a semiconductor and the subsequent selective removal of patterns from each layer. Lam holds the top market share in etch and holds the clear second share in deposition. It is more exposed to memory chipmakers for DRAM and NAND chips. It counts as top customers the largest chipmakers in the world, including TSMC, Samsung, Intel, and Micron.

More About Our LRCX ML Model...

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

To train our stocks LRCX 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 LRCX 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 LRCX 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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