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Top Deep Learning Companies in Piscataway


2 Companies

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Futurism Technologies, Inc.

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Futurism Technologies is a CMMI Level 3 and ISO 9001:2015 and ISO 27001 certified organization. A leading provider of digital information technology, consulting, cyber security, and digital transformation services. Headquartered in Piscataway, New Jersey (U.S.), Futurism takes great pride in its ability to provide a guidance and definition to their clients’ digital journey. Established in 2003, Futurism Technologies has a global presence including USA, UAE, Australia, Germany and India. With over 10 global development and delivery centers worldwide and approximately 750+ employees, Futurism is a member of the NASSCOM group and is ranked among the top-performing and fastest-growing digital transformation companies in the USA.

  • dollar

    $25-49/hr

  • user

    500 to 999

  • calender

    2003

  • location

    United States (USA)

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UniqAI Solutions

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Transform Your Business with UniqAI Solutions UniqAI Solutions provides cutting-edge AI development services that help businesses automate processes, optimize decision-making, and enhance value through tailored digital solutions. Whether you're a large enterprise, a growing SME, or an innovative startup, our expertise in AI technology enables you to stay ahead in a rapidly changing market. Partner with us to unlock the power of AI and drive sustainable success for your organization.

  • dollar

    $50-99/hr

  • user

    10 to 49

  • calender

    2024

  • location

    United States (USA)

Frequently Asked Questions

Deep Learning is a subset of Artificial Intelligence that uses neural networks with multiple layers to learn from large amounts of data. It's particularly effective for tasks like image and speech recognition.

Deep Learning can automatically discover the features to be used for classification, while traditional Machine Learning requires manual feature engineering. Deep Learning also generally performs better with large amounts of data.

Deep Learning is used in various business applications, including customer service chatbots, fraud detection, personalized recommendations, and predictive maintenance in manufacturing.

Deep Learning typically requires large amounts of labeled data. The type of data depends on the project, but it can include images, text, audio, or numerical data.

The implementation time can vary greatly depending on the complexity of the problem, the amount of data available, and the expertise of the team. It can range from a few weeks to several months.

Some drawbacks include the need for large amounts of data, high computational requirements, the "black box" nature of decision-making, and potential biases in the training data.

Deep Learning often outperforms other AI techniques in tasks involving unstructured data like images or text, especially when large datasets are available. However, for simpler tasks or with limited data, traditional machine learning methods may be more suitable.

Deep Learning often requires powerful GPUs or specialized hardware, substantial storage for large datasets, and robust cloud computing resources. The specific needs depend on the scale and complexity of the project.

Businesses should focus on data privacy, model transparency, regular bias checks, and establishing clear guidelines for the use and deployment of Deep Learning systems. It's also important to have human oversight and intervention mechanisms.

A successful Deep Learning team typically needs data scientists, machine learning engineers, software developers, domain experts, and data engineers. Skills in Python, neural network architectures, and big data technologies are often required.

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