If You Can Only Buy One Machine Learning Stock in December, It Better Be One of These 7 Names

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  • The strongest names in Silicon Valley are the best choices among machine learning stocks.
  • Alphabet/Google (GOOG,GOOGL): Google’s machine learning and AI research are among the best in the world.
  • ASML (ASML):  ASML is using machine learning to improve its industry leading chip manufacturing machines.
  • Microsoft (MSFT): Microsoft has multiple products dedicated to machine learning.
  • Nvidia (NVDA): Nvidia’s lead in all things ML and AI should increase due to its h200 chips.
  • AMD (AMD): AMD continues to be a dark horse but one worth considering in relation to ML.
  • Amazon (AMZN): Amazon’s machine learning platforms have wide enterprise application.
  • Snowflake (SNOW): Snowflake is incredibly well positioned among machine learning growth stocks.
Machine Learning Stock - If You Can Only Buy One Machine Learning Stock in December, It Better Be One of These 7 Names

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Machine learning is a subfield of artificial intelligence. It is focused on enabling computers to learn from data without being programmed to do so. In shorts, machine learning is the process that enables AI to exist. Thus, the stocks that investors are considering in the field are essentially AI stocks. If you are in the market for an AI stock or a machine learning stock, take a look at the ones we have here!

Is a strong argument to be made that sticking with the biggest Silicon Valley firms is the way to go. Those firms have invested heavily into machine learning and artificial intelligence. They are currently reaping the benefits of that investment and should continue to do so. Thus, if you can only buy a single machine learning stock in December, it should be one of these firms listed below.

Alphabet/Google (GOOG,GOOGL)

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Alphabet/Google (NASDAQ:GOOG,GOOGL) Hasn’t received as much attention in regard to machine learning as some of its peers. However, it would be a big mistake to disregard the company and its stock in relation to machine learning.

It goes without mentioning but Google is utilizing AI to improve its search function and other products that are integral to the stock and its performance. Google’s machine learning platform is called TensorFlow. TensorFlow Is an open source framework used in machine learning applications.

Further, Google and its parent company, Alphabet, obviously have deep pockets and an innate interest in artificial intelligence. The company has used those resources to create what is one of the most respected AI research divisions in Silicon valley.

There’s absolutely no reason to discount Google in relation to machine learning and AI. On top of that, Google’s advertising revenues are getting stronger by the day. With peak rates at hand, it’s logical to assume that those revenues will only be strengthening moving forward. 

ASML (ASML)

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ASML (NASDAQ:ASML) He’s well known as one of the more unique and best positioned semiconductor firms globally. Its lithography machines are bus-sized pieces of equipment that can cost several hundred million dollars. It essentially has no rivals so that makes its stock perpetually interesting.

ASML is applying machine learning to understand how to improve its already strong position. The company is applying those results in order to figure out how to improve those machines. further it is applying AI to better understand the maintenance needs required for those lithography machines.

In general, ASML is one of the better stocks to consider in regard to AI and machine learning currently. companies of all sizes are going to require greater and greater quantities of higher performance chips. asml’s machines are at the leading edge of that production.

It continues to be an excellent picks-and-shovels investment in the overall growth of AI. Further, ASML is a very stable company and provides a modest amount of income through a dividend yielding 0.8%.

Microsoft (MSFT)

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Microsoft (NASDAQ:MSFT) deservedly continues to receive a lot of attention in regard to machine learning and artificial intelligence. The company offers several machine learning products. Those products include Azure Machine Learning and Cognitive Services.

Azure Machine Learning Is a set of cloud-based machine learning tools used to build machine learning models. It allows users to engage in tasks vital to machine learning including classification, clustering and regression.

Cognitive Services Is a set of APIs focused on language, speech, and vision. Microsoft continues to make leading technology and deploy that technology across the enterprise space. The company has established  a very strong foothold in the AI space in 2023. Its investment in OpenAI will continue to pay dividends for a long time. Speaking of dividends, Microsoft continues to pay a very modest dividend, but one that continues to grow.

There’s no compelling reason not to invest in Microsoft for the long-term.

Nvidia (NVDA)

Nvidia corporation (NVDA) logo displayed on smartphone with stock market chart background. Nvidia is a global leader in artificial intelligence hardware and software
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Every investor realizes that Nvidia’s (NASDAQ:NVDA)  chips have become a must-have for all things artificial intelligence. Its stock has skyrocketed in 2023 for that reason. The company continues to garner headlines for that reason as well.

Nvidia’s leading chips are also highly applicable to machine learning. The company is known for its dominant GPUs, or graphic processing units. Basically, any firm with any interest in artificial intelligence and machine learning, which is almost every company, demands Nvidia’s chips.

That strong demand has resulted in incredible prices for Nvidia’s H100 chips which dominate the space. Those chips are known to be the industry standard and companies simply have to do what they can to secure their supply of the chips. The difference between Nvidia’s chips and those of its competitors matters. 

That gap is only going to grow in the future because the company has just announced its H200 GPU. that chip will have even greater performance specifications applicable to machine learning and AI. Therefore, it’s reasonable to anticipate another period of massive demand as enterprises of all sizes scramble to secure H200 chips. This is the machine learning stock everybody is talking about, and for good reason.

AMD (AMD)

In this photo illustration, the AMD logo is shown on a smartphone screen.
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AMD (NASDAQ:AMD) is admittedly far behind Nvidia in most respects. That’s also true of its machine learning capabilities. Nonetheless, the stock continues to be one to consider in regard to machine learning.

Earlier in 2023, the company captured headlines in relation to its pursuit of Nvidia in machine learning capability. At that time, it was assumed that AMD’s chips were roughly 80% as powerful as Nvidia’s for machine learning applications. 

As mentioned, Nvidia just announced that it will be releasing new and improved H200 chips. Those chips are slated to be released in the second quarter of 2024. That means AMD will have to provide some sort of technological Leap Forward in that time frame in order not to fall farther behind.

That said, AMD’s chips continue to have lots of applications across the machine learning space. firms are using its chips for applications such as natural language processing, fraud detection, and other uses such as computer vision.

Amazon (AMZN)

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Amazon (NASDAQ:AMZN) Is known primarily as an e-commerce stock. Additionally, Amazon is among the leading cloud computing firms globally. it has a strong, deep position in the machine learning world that makes it a compelling choice overall.

Amazon is applying machine learning across its operations. Machine learning is used by the company to  improve product recommendations for e-commerce customers. The company is applying machine learning in its AWS Cloud operations as well. Amazon web services is one of the leading platforms for the deployment of machine learning. 

The company offers several machine learning products for enterprise customers. Those products, including Amazon SageMaker, allow developers to Create and train machine learning models. the company’s deep ability in this regard make it among the best long-term choices for machine learning investors. 

Beyond that, the business cycle also favors Amazon at the moment. The markets seem to have avoided the worst outcome and are instead headed toward future rate cuts. that promises to bring more and more customers both on the e-commerce and machine learning sides.

Snowflake (SNOW)

Snowflake symbol and logo at the company corporate headquarters in Silicon Valley. SNOW stock.
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Snowflake (NASDAQ:SNOW) Is fairly similar to Amazon in relation to machine learning. However, Snowflake does not engage in e-commerce, and instead is solely a cloud company.

The company offers Machine learning capabilities across three main areas. SnowPark ML allows developers to build ML models using Python language. It also offers a space to store the building blocks of those models which are then further developed. Further, Snowflake features the ability to integrate external ml models created elsewhere. Thus, it’s clear that Snowflake is heavily invested in pulling customers away from the larger cloud machine learning firms.

That’s an interesting angle to snowflake because switching costs are extraordinarily high in the machine learning space.

Overall, investors should consider Snowflake as one of the best machine learning stocks to purchase in December. The company is growing at an extraordinarily fast rate. Investors would be hard pressed to find a better positioned growth stock  with a heavy ML presence to take advantage of upcoming rate cuts.

On the date of publication, Alex Sirois did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

Alex Sirois is a freelance contributor to InvestorPlace whose personal stock investing style is focused on long-term, buy-and-hold, wealth-building stock picks. Having worked in several industries from e-commerce to translation to education and utilizing his MBA from George Washington University, he brings a diverse set of skills through which he filters his writing.


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