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as 06-14-2024 4:00pm EST

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Stocks

Technology

Computer Software: Programming Data Processing

Nasdaq

VNET started as AsiaCloud in 1999 and moved to the data center business with its first self-developed data center opening in 2010. The firm listed (as 21Vianet) on the Nasdaq in April 2011, subsequently changing its name to VNET Group in 2021. It originally focused on providing data center services such as colocation and cloud services to retail clients in China, but added hyperscale customers in 2019 and now counts large Chinese hyperscalers such as Alibaba Cloud, Tencent Cloud, and Huawei Cloud as customers. At end-December 2023 it had 89,357 self-built cabinets with the majority in Beijing, Shanghai, and the Greater Bay area. It also operated partnered data centers with around 4,240 cabinets and had 476 MW of wholesale capacity contracted or under a memorandum of understanding.

More About Our VNET ML Model...

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

To train our stocks VNET 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 VNET 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 VNET 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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