3 Machine Learning Stocks That Could Make Your February Unforgettable

Stocks to buy

Machine learning stocks are only going to become more valuable over time, thanks in part to the AI revolution as well as the expanding use case for these companies. I think that many investors can benefit from having at least some shares of machine learning stocks in their portfolios.

For this article, I’ve handpicked three of the best machine learning stocks for investors to consider. I narrowed down this list by looking for brands with the most promising prospects and potential upside for their stock prices.

So here are the best machine learning stocks for investors to consider.

Nvidia (NVDA)

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Nvidia (NASDAQ:NVDA) stands out in the machine learning landscape, especially after acquiring OmniML to enhance machine learning model deployment for developers and organizations.

This year, NVDA stock plans on integrating machine learning more deeply for surgery, drug discovery, enterprise data processing and consumer experience use cases. The company will accomplish this by leveraging large language models and generative AI. Additionally, Nvidia focusing on hyper-scale accelerators to boost machine learning throughput for web data centers, addressing the growing demand for AI capabilities in web applications.

Although the company trades at 95 times earnings, recent analyst estimates for the stock give it a substantial implied upside. For example, Vijay Rakesh from Mizuho maintained his $825 price target, while C J Muse from Cantor Fitzgerald rated the stock as “Buy” and reiterated his $775 target.

UiPath (PATH)

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UiPath (NYSE:PATH) outlined its financial outlook for 2024. The company expects revenue in the range of $381 million to $386 million for the fourth quarter of fiscal 2024, with an Annual Recurring Revenue (ARR) in the range of $1.450 billion to $1.455 billion as of Jan. 31, 2024.

This projection indicates a strong growth trajectory, supported by a year-over-year increase of 24% in revenue and ARR for the third quarter of fiscal 2024.

At present, PATH’s stock price stands at $24.94, marking a slight decrease of 7.22% over the past five days but an overall increase of 0.40% since the beginning of the year. Despite the somewhat muted share price movement, some analysts categorize it as a “sleeper hit” amidst the AI frenzy.

In terms of valuation, the forward P/E ratio stands at approximately 47 to 55 times earnings, suggesting expectations of earnings growth within the next twelve months, and it trades at around 11 times sales at the time of writing.
I think that PATH is a buy, given its EPS is forecasted to grow by 10.68% next financial year. Additionally, its top line could swell to $1.31 billion, up 23.94%

SoundHound AI (SOUN)

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SoundHound AI (NASDAQ:SOUN) is another one of those machine learning stocks that are poised for significant growth this year. The company expects a significant revenue increase of approximately 50% in 2023, with projections ranging from $43 to $50 million.

Also, SoundHound AI plans on becoming adjusted EBITDA positive in the fourth quarter of 2023, thanks to a restructuring expected to save approximately $60 million in operating costs.

On the valuation front, SOUN stock also looks attractive. Its forward price-to-sales ratio of 8 times sales is significantly below the median of its peers, suggesting that it may be undervalued relative to them.

There have been some recent analyst upgrades for SOUN stock, which could be leaving investors feeling bullish about the company. For instance, Glenn Mattson from Ladenburg Thalmann gave it a “strong buy” rating last month, along with a 75.82% forecasted increase for its stock price to $4. 

With it on track to being EBITDA positive in the near future, SOUN is one of those machine learning stocks to buy.

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

Matthew started writing coverage of the financial markets during the crypto boom of 2017 and was also a team member of several fintech startups. He then started writing about Australian and U.S. equities for various publications. His work has appeared in MarketBeat, FXStreet, Cryptoslate, Seeking Alpha, and the New Scientist magazine, among others.

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