3 machine learning stocks to buy that could explode

Machine Learning


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In the age of artificial intelligence (AI) and advanced technology, machine learning (ML) has emerged as a game changer. ML is revolutionizing industries and driving businesses forward. As organizations strive to stay on the cutting edge, three companies stand out as pioneers in harnessing the power of ML.

Of note, the first company is focused on operationalizing AI and ML models. Bridge the gap between experiments and real-world implementations. The second, by contrast, tackles the formidable challenge of cybersecurity. Leverage ML models trained on massive amounts of data to detect and prevent threats in real time. while the third leverages ML and natural language processing (NLP) to automate tasks, provide intelligent recommendations, and enhance operational intelligence.

This article explores the explosive upside potential of investing in these companies. It also expands the new value possibilities they are creating.

Palantir Technologies (PLTR)

Palantir (PLTR) logo inside a smartphone with a series of stock charts in the background.

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Palantir Technologies (New York Stock Exchange: PLTR) focuses on the operationalization of AI and ML models and aims to address the long-term challenges organizations face in managing these models. Additionally, Palantir deploys its models on top of a trusted data foundation. It is continuously improved based on user decisions and feedback. The company aims to bridge the gap between AI and ML experiments and real-world implementations.

Interestingly, one of the main strengths of Palantir’s approach is the end-to-end infrastructure that unlocks the value of compound interest. The company’s platform provides a secure data foundation that integrates data from various sources and provides fine-grained access control policies. The result is data security and transparent governance. Additionally, Palantir’s interconnected micro-model ecosystem enables organizations to address discrete parts of complex problems and combine them to create solutions. This approach improves model performance and reduces concept and data drift.

Palantir’s Model Goals feature also enables organizations to tie business logic to specific Key Performance Indicators (KPIs) and deploy models consistently across use cases. Additionally, the ontology within the Palantir platform facilitates interaction between the model and the rest of the system.

Additionally, Palantir’s production deployment infrastructure, AI for the Internet of Things (IoT), and edge capabilities meet the growing need for real-time decision-making and edge computing. Supports model customization, deployment, evaluation, and comparison across different tools and environments. With this, Palantir enables customers to leverage their preferred AI and ML solutions. At the same time, you benefit from the platform’s integration capabilities and continuous health monitoring.

Finally, Palantir’s foundry-driven AI and ML solutions are demonstrating value in a variety of areas, including discovering investigative leads, streamlining biomedical research, analyzing IoT sensor data, and enhancing decision-making in manufacturing. .

CrowdStrike Holdings (CRWD)

The CrowdStrike sign and logo at our Silicon Valley headquarters.  CRWD stock.

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Crowdstrike Holdings (Nasdaq: CRWDMore) leverages vast amounts of behavioral and contextual data to train ML models to detect malicious activity with high accuracy.

Specifically, Crowdstrike’s ML approach involves training models on the extensive telemetry of the CrowdStrike Security Cloud to correlate trillions of data points. This allows us to provide greater visibility and refine our threat intelligence. ML models also automate threat detection and response, augment human expertise, and improve analyst efficiency.

Additionally, the company combines agent-based and cloud-native models to deploy multiple layers of defense to quickly stop threats. Crowdstrike detects and stops threats in real time by leveraging behavioral analytics, real-time sensor telemetry, and AI-powered indicators of attack (IOAs). Additionally, the company’s Falcon OverWatch team of threat hunters utilizes AI-generated alert signals and advanced tools to investigate and stop advanced threats.

Crowdstrike also focuses on combating hands-on keyboard attacks that pose a greater risk than traditional malware-based attacks. ML models trained on behavioral event data can detect and predict negative patterns in real time, regardless of specific tools or malware. Additionally, AI and ML can help identify emerging threats and help security teams prevent breaches.

CrowdStrike has introduced Charlotte AI, a generative AI security analyst, to further enhance its capabilities. Charlotte AI leverages high-quality security data and continuous feedback from threat hunters and incident response experts to deliver intuitive answers and insights for users of all skill levels. The result is security democratization, enabling better decision-making, threat understanding and task automation.

Finally, Crowdstrike is a leader in managed detection and response (MDR) services that use AI and generative AI to revolutionize cybersecurity. Through collaboration with Amazon’s (Nasdaq:AMZN) AWS, Crowdstrike, aims to develop powerful generative AI applications that accelerate customers’ cloud, security, and AI initiatives. They leverage AWS’ generative AI capabilities and cloud services to power the Falcon platform’s search, reporting, and automation capabilities.

ServiceNow (now)

ServiceNow office building in Silicon Valley.

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Service Now (New York Stock Exchange: now) employs ML and NLP to automate tasks, accelerate problem resolution, and provide intelligent recommendations. The company’s AI capabilities are built on classification, similarity, clustering, and regression analysis frameworks, enabling automatic classification, smart recommendations, incident detection, pattern identification, and accurate time-to-resolution predictions. to Additionally, ServiceNow’s recent acquisition of G2K, aimed at integrating smart IoT technology into their platform, was initially targeted at the retail industry, but could have applications in other areas. .

The Tokyo release of the ServiceNow platform introduces solutions that improve operational intelligence and reliability. These solutions leverage AI, automation, and risk management to enhance efficiency, business intelligence, and resilience. Examples include Task Intelligence in Customer Service Management, which automates tasks and prioritizes cases based on sentiment analysis, and Automation Center, which provides visibility into organizational automation for cost savings. In addition, ServiceNow’s enhanced Now Platform offers innovative solutions such as financial and supply chain workflows, generative AI solutions for intelligent automation, and AI-powered employee growth and development solutions that drive talent transformation. Bring innovation.

To address the complexity of cloud infrastructure, ServiceNow offers cloud observability solutions that enable effective management of cloud environments. He also founded ServiceNow.org, a program to digitally transform nonprofits through simplified solutions. Additionally, ServiceNow has deepened partnerships with: microsoft (Nasdaq:MSFTMore), integrating Now Platform with Azure Open AI A service that provides generative AI capabilities for increased productivity and accurate results.

Meanwhile, ServiceNow’s RiseUp with ServiceNow program focuses on skills development and talent transformation. We have also expanded our training curriculum to include Microsoft courses and other partner courses, expanding the talent pool for organizations. Finally, ServiceNow aims to drive customer growth by leveraging AI/ML innovations.

As of the date of issue, Yannis Turpanos did not hold (directly or indirectly) any positions in the securities referred to in this article. The opinions expressed in this article are those of the author and are subject to InvestorPlace.com Publishing Guidelines.

Yiannis Zourmpanos is the founder of Yiazou Capital Research, an equity market research platform designed to improve the due diligence process through in-depth business analysis.

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This article first appeared on InvestorPlace 3 machine learning stocks to buy with explosive upside potential.

The views and opinions expressed herein are those of the authors and do not necessarily reflect those of Nasdaq, Inc.



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