3 Machine Learning Stocks That Could Be Multi-Baggers in the Making: February Edition

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    Much like artificial intelligence, machine learning has become essential for companies all around the world. Better, as more companies wake up to the opportunity, it’s creating massive opportunity for machine learning stocks.

    Look at Netflix (NASDAQ:NFLX), for example. The company saved about $1 billion thanks to its “machine learning algorithm for the combined effect of personalization and content recommendations,” noted G2 Learn Hub. They added, “A 60% reduction in Google Translate errors was found when changed to GNMT—a translation algorithm powered by machine learning.”

    Better, as demand picks up from most industries, machine learning could be a $528.1 billion market by the time 2030 rolls around, says Statista. All of which could have a substantial impact on machine learning stocks such as these.

    Nvidia (NVDA)

    Nvidia logo seen on smartphone which is placed on pile of US dollar bills. Concept. Selective focus. Stocks to buy like Nvidia

    Source: Ascannio / Shutterstock.com

    Machine learning stocks, like Nvidia (NASDAQ:NVDA) trade at $700 at the moment. However, I strongly believe it’s headed to at least $1,000, even $1,500 this year. All thanks to its dominance with artificial intelligence and machine learning, where its graphic processing units (GPU) are considered to be “more powerful and can provide better performance for machine learning tasks,” according to a LinkedIn article.

    NVDA earnings have been just as explosive with adjusted EPS coming in at $5.16, compared to expectations for $4.64. Revenue of $22.1 billion also exceeded expectations for $20.62 billion. For its current quarter, the company expects to see sales of $24 billion as compared to estimates for $22.2 billion. That’s up significantly from the $7.19 billion in sales posted a year earlier.

    Plus, according to CFO Colette Kress, the supply of current artificial intelligence GPUs is improving and demand is strong. Plus, the company expects its “next-generation products to be supply constrained as demand far exceeds supply,” as noted by Barron’s.

    Advanced Micro Devices (AMD)

    Advanced Micro Devices, Inc. (AMD) logo in the building at CNE in Toronto. AMD is an American semiconductor company.

    Source: JHVEPhoto / Shutterstock.com

    Advanced Micro Devices (NASDAQ:AMD) is also benefiting from the machine learning and AI boom. From its current price of $164.29, I’d like to see it closer to $200. Helping, AMD’s RDNA 3 GPU architecture “includes upgraded machine learning accelerators that are more than twice as fast as its previous-generation technology,” as noted by SiliconANGLE, as I noted on Jan. 27.

    In addition, its MI300 chips are poised to rival Nvidia’s H100 chips, some of the most powerful AI chips on the market. Microsoft and Meta Platforms have already said they’ll use AMD’s MI300 chips as an alternative to “the expensive Nvidia graphics processors that have been essential for artificial intelligence,” as noted by CNBC.

    iShares U.S. Technology ETF (IYW)

    iShares by Blackrock sign

    Source: Sundry Photography / Shutterstock.com

    If you want to diversify with about 133 holdings, there’s always an exchange-traded fund (ETF) such as iShares U.S. Technology ETF (NYSEARCA:IYW).

    Since late October, the IYW ETF ran from about $102.50 to a high of about $135. Howev I’d like to see it closer to $160 this year. With an expense ratio of 0.40%, the fund tracks U.S. electronics, computer software and hardware and informational technology stocks. Some of its top holdings include Nvidia, Microsoft (NASDAQ:MSFT), Apple (NASDAQ:AAPL) and Meta Platforms (NASDAQ:META) to name a few.

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

    Ian Cooper, a contributor to InvestorPlace.com, has been analyzing stocks and options for web-based advisories since 1999.

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