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Using natural language processing (NLP), machine learning (ML), Generative AI, and other AI technologies and platforms; Analyzing Conversational (Chats, Emails, Messages and Calls) data, and the use of this data to build Natural Language (NLP) modeling pipelines for intent classification, training & deploying conversational AI systems, IVR, virtual assistants, chatbots etc.
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The Data & Analytics department in Legal and Compliance is responsible for designing and optimizing surveillance models, approaches and tools using advanced analytical techniques like supervised and unsupervised machine learning, Natural Language Processing (NLP) and evolving techniques like reinforcement and deep learning as well as graph analytics.
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Experience with Large Language Models (LLM) and Natural Language Processing (NLM), RAG (Retrieval Augmented Generation). The Senior Data Scientist should have experience working with AWS cloud environments with tools such as AWS Sagemaker, AWS Lambda, Amazon Aurora, Amazon Athena, Bedrock, and Amazon Kendra.
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Moderate experience with machine learning and natural language processing. Strong experience with key programming and visualization tools like Java, R, SQL and Power BI. Knowledge of R-Shiny preferred.
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Use advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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Strong working knowledge of applying data analysis algorithms (data mining, statistics, machine learning, natural language processing, sentiment analysis, text mining, etc.) Being an expert on the latest health and wellness technology, products and use cases related to AI, big data, responsible AI (Artificial Intelligence) / Machine Learning (ML), and Internet of Things (IoT.
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Experience in Machine Learning (ML), Natural Language Processing (NLP), spaCy and NLTK, as well as language models like BERT and RoBERTa, are highly desired. Experience in Machine Learning (ML), Natural Language Processing (NLP), spaCy and NLTK, as well as language models like BERT and RoBERTa, are highly desired.
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Natural Language Processing (NLP): Extensive experience in developing NLP models for processing unstructured text data. Proven skills in statistics, data processing, or data annotation.
$144,024 a yearPart-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Proficiency with deep learning tools and at least one machine learning tool, such as Hadoop, Apache Spark, TensorFlow, scikit-learn, or cloud-provider equivalents. Proven ability to work with at least one machine learning tool like Hadoop, Apache Spark, TensorFlow, or scikit-learn, or cloud-provider equivalents.
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General Description The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning.
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Text mining and Natural Language Processing (NLP) is preferred. Knowledge of databases, data structures, data processing and data mining from large enterprise transaction systems (e.g., Epic, Infor/Lawson, McKesson HPM, Payer Claims or similar applications in healthcare or other industries.
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Development processes for natural language processing, machine learning on. processing platforms, and security; Provide assistance, and resolve. By blending technology with our industry expertise, we're able to harness the potential of Cloud, AI, ML, IoT, 5G, and quantum computing to design and implement real-world solutions for a variety of business problems.
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Involvement in the analyses of unstructured and semi-structured data, employing advanced techniques such as latent semantic indexing (LSI), natural language processing (NLP), and exploratory data analysis (EDA.
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Experience in designing and implementing machine learning models, natural language processing (NLP), computer vision applications, and other AI technologies preferred. Deep Learning and Machine Learning using frameworks, such as TensorFlow or PyTorch etc.
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Candidates should have a deep understanding of AI technologies, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning.
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natural language processing jobs in Rosedale, MD
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