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    Results for "machine learning in distributed environments"

    • Status: Free Trial
      Free Trial
      I

      IBM

      AI Workflow: Enterprise Model Deployment

      Skills you'll gain: Apache Spark, Data Pipelines, MLOps (Machine Learning Operations), PySpark, Application Deployment, IBM Cloud, Machine Learning, Containerization, Data Science, Python Programming, Performance Tuning, Scalability

      4.3
      Rating, 4.3 out of 5 stars
      ·
      58 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Preview
      Preview
      N

      Northeastern University

      Machine Learning for Engineers: Algorithms and Applications

      Skills you'll gain: Supervised Learning, Statistical Machine Learning, Machine Learning Algorithms, Unsupervised Learning, PyTorch (Machine Learning Library), Applied Machine Learning, Statistical Methods, Statistical Modeling, Machine Learning, Statistical Analysis, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Regression Analysis, Algorithms, Predictive Modeling, Dimensionality Reduction, Complex Problem Solving

      Intermediate · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Developing AI Applications on Azure

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Microsoft Azure, Applied Machine Learning, Python Programming, Machine Learning, Machine Learning Algorithms, Data Science, Image Analysis, Computer Vision, Application Deployment, Natural Language Processing, Application Programming Interface (API)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      978 reviews

      Advanced · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      W

      Whizlabs

      Azure ML: Designing and Preparing Machine Learning Solutions

      Skills you'll gain: Data Management, Data Pipelines, Continuous Monitoring

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Machine Learning with Spark on Google Cloud Dataproc

      Skills you'll gain: Apache Spark, Google Cloud Platform, Predictive Modeling, Big Data, Applied Machine Learning, Cloud Computing, Statistical Modeling

      Intermediate · Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Device-based Models with TensorFlow Lite

      Skills you'll gain: iOS Development, Android Development, Tensorflow, Swift Programming, Mobile Development, Applied Machine Learning, Embedded Systems, Machine Learning Methods, Computer Vision, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      653 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      W

      Whizlabs

      Azure ML: Deploying, Managing, and Experimenting with Models

      Skills you'll gain: Microsoft Azure, MLOps (Machine Learning Operations), Data Management, Cloud Computing, Application Deployment, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Performance Tuning, Automation

      Advanced · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Running Distributed TensorFlow using Vertex AI

      Skills you'll gain: Tensorflow, Google Cloud Platform, Image Analysis, Applied Machine Learning, MLOps (Machine Learning Operations), Cloud Computing, Distributed Computing

      Intermediate · Project · Less Than 2 Hours

    • Status: New
      New
      Status: Preview
      Preview
      C

      Coursera Instructor Network

      Operationalizing ML Models: MLOps for Scalable AI

      Skills you'll gain: MLOps (Machine Learning Operations), CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Containerization, Scalability, Continuous Integration, DevOps, Data Infrastructure, IT Infrastructure, Infrastructure Architecture, Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Continuous Monitoring, Real Time Data, Version Control

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      AI Workflow: AI in Production

      Skills you'll gain: Application Deployment, MLOps (Machine Learning Operations), Unit Testing, Containerization, Workflow Management, IBM Cloud, Machine Learning, Performance Analysis, Business Metrics, Natural Language Processing, Time Series Analysis and Forecasting, Continuous Monitoring, Data Science, Python Programming, Design Thinking

      4.4
      Rating, 4.4 out of 5 stars
      ·
      53 reviews

      Advanced · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Distributed Image Processing in Cloud Dataproc

      Skills you'll gain: Apache Spark, PySpark, Google Cloud Platform, Cloud Management, Cloud Computing, Distributed Computing, Package and Software Management

      Intermediate · Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Machine Learning Foundations for Product Managers

      Skills you'll gain: Deep Learning, Unsupervised Learning, Classification And Regression Tree (CART), Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Decision Tree Learning, Computer Vision, Supervised Learning, Natural Language Processing, Random Forest Algorithm, Data Science, Predictive Analytics, Algorithms, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      606 reviews

      Intermediate · Course · 1 - 3 Months

    1…8910…834

    In summary, here are 10 of our most popular machine learning in distributed environments courses

    • AI Workflow: Enterprise Model Deployment: IBM
    • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
    • Developing AI Applications on Azure: LearnQuest
    • Azure ML: Designing and Preparing Machine Learning Solutions: Whizlabs
    • Machine Learning with Spark on Google Cloud Dataproc: Google Cloud
    • Device-based Models with TensorFlow Lite: DeepLearning.AI
    • Azure ML: Deploying, Managing, and Experimenting with Models: Whizlabs
    • Running Distributed TensorFlow using Vertex AI: Google Cloud
    • Operationalizing ML Models: MLOps for Scalable AI: Coursera Instructor Network
    • AI Workflow: AI in Production: IBM

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