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  • Integration Of Ml In Ids

Results for "integration+of+ml+in+ids"


  • C

    Coursera

    Integrate, Scale, and Monitor ML Microservices

    Skills you'll gain: Microservices, MLOps (Machine Learning Operations), Application Performance Management, AI Integrations, Site Reliability Engineering, AI Workflows, Continuous Monitoring, Performance Analysis, Event-Driven Programming

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Multimodal Intelligence - Vision, Audio & Language in Action

    Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, API Design, Multimodal Prompts, Data Preprocessing, Vision Transformer (ViT), Data Processing, Solution Architecture, Kubernetes, Apache Airflow, Transfer Learning, PyTorch (Machine Learning Library), Data Pipelines, CI/CD, Model Evaluation, Deep Learning, Natural Language Processing, Computer Vision, Docker (Software), Ethical Standards And Conduct

    Intermediate · Professional Certificate · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Tokens to Deployment: NLP, Language Models, & Production API

    Skills you'll gain: OAuth, Unit Testing, Apache Airflow, Fine-tuning, Model Evaluation, Data Validation, API Design, Test Driven Development (TDD), Data Integrity, Extract, Transform, Load, Multimodal Prompts, Natural Language Processing, MLOps (Machine Learning Operations), OpenAI API, Data Presentation, Hugging Face, Token Optimization, LLM Application, CI/CD, Tensorflow

    Intermediate · Specialization · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • M

    Microsoft

    Microsoft AI & ML Engineering

    Skills you'll gain: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Data Infrastructure, Data Preprocessing, Model Optimization

    ★ 4.6 (358) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Unit Testing, Responsible AI, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    ★ 4.2 (606) · Advanced · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • K

    KodeKloud

    Hands-On MLOps Fundamentals for ML Engineers

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Training, Amazon Web Services, Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Machine Learning, Data Governance, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Automation, Unsupervised Learning

    Beginner · Specialization · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • C

    Coursera

    Production ML Engineering: Packaging, APIs, and Testing

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Software Documentation, Code Reusability, Model Training, Test Script Development, Continuous Delivery, Test Automation, Model Evaluation, Continuous Integration, Technical Documentation, API Design, Application Programming Interface (API), Data Validation, Applied Machine Learning, Machine Learning Methods, Maintainability, Version Control, Package and Software Management, Code Review

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • B

    Board Infinity

    MLOps and LLMOps: Deploying and Scaling AI in Production

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, LLM Application, Application Deployment, Model Training, Cloud Deployment, Continuous Deployment, AI Workflows, AI Security, Data Ethics, Responsible AI, Prompt Engineering, Retrieval-Augmented Generation, Scalability, CI/CD, Site Reliability Engineering, Model Evaluation, Release Management, System Monitoring, Containerization

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • P

    Pragmatic AI Labs

    Machine Learning with Databricks and MLflow

    Skills you'll gain: MLOps (Machine Learning Operations), Databricks, Apache Spark, Model Evaluation, Hugging Face, Data Architecture, Recurrent Neural Networks (RNNs), LLM Application, Data Science, Data Mining, Mathematical Modeling, Scala Programming, Continuous Monitoring, Rust (Programming Language), Lean Six Sigma, Statistical Inference, Artificial Intelligence, Functional Testing, Exploratory Data Analysis, Programming Principles

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    Machine Learning with Apache Spark

    Skills you'll gain: Apache Spark, Machine Learning, Generative AI, Model Evaluation, Supervised Learning, Apache Hadoop, Data Pipelines, Unsupervised Learning, Data Processing, Extract, Transform, Load, Predictive Modeling, Model Deployment, Classification Algorithms, Data Transformation, Regression Analysis

    ★ 4.5 (114) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Production-Ready Multimodal ML Engineering

    Skills you'll gain: MLOps (Machine Learning Operations), Data Validation, Model Deployment, Test Driven Development (TDD), Apache Airflow, Data Pipelines, Containerization, Extract, Transform, Load, Kubernetes, Model Training, Data Integrity, Model Optimization, Cloud-Native Computing, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Software, Artificial Intelligence, Artificial Neural Networks, Machine Learning Algorithms, Natural Language Processing, Algorithms

    Intermediate · Course · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • E

    Edureka

    Getting Started with Automated Machine Learning (AutoML)

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Optimization, Automation, Artificial Intelligence and Machine Learning (AI/ML), Model Training, Machine Learning Methods, No-Code Development, Data Preprocessing, Scikit Learn (Machine Learning Library), Machine Learning, Model Evaluation, Applied Machine Learning, Predictive Modeling, Feature Engineering, Data-Driven Decision-Making, Machine Learning Algorithms, Artificial Intelligence, Data Validation, Data Quality

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
1234…9

In summary, here are 10 of our most popular integration+of+ml+in+ids courses

  • Integrate, Scale, and Monitor ML Microservices: Coursera
  • Multimodal Intelligence - Vision, Audio & Language in Action: Coursera
  • Tokens to Deployment: NLP, Language Models, & Production API: Coursera
  • Microsoft AI & ML Engineering: Microsoft
  • MLOps | Machine Learning Operations: Duke University
  • Hands-On MLOps Fundamentals for ML Engineers: KodeKloud
  • Production ML Engineering: Packaging, APIs, and Testing: Coursera
  • MLOps and LLMOps: Deploying and Scaling AI in Production: Board Infinity
  • Machine Learning with Databricks and MLflow: Pragmatic AI Labs
  • Machine Learning with Apache Spark: IBM

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