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  • Machine Learning Model Lifecycle

Results for "machine learning model lifecycle"


  • W

    Whizlabs

    Fundamentals of Machine Learning

    Skills you'll gain: Supervised Learning, Unsupervised Learning, MLOps (Machine Learning Operations), Model Optimization, Applied Machine Learning, Machine Learning Methods, Model Evaluation, Model Training, Data Preprocessing, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Machine Learning Algorithms, Model Deployment, Microsoft Azure, Amazon Web Services, Cloud Solutions, Deep Learning, Data Processing

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • W

    Whizlabs

    Azure ML: Deploying, Managing, and Experimenting with Models

    Skills you'll gain: Model Deployment, Responsible AI, Microsoft Azure, MLOps (Machine Learning Operations), Data Management, Model Optimization, Cloud Management, Model Training, Cloud Deployment, Data Store, Data Strategy, Applied Machine Learning, Model Evaluation, Scalability, Data Preprocessing, Machine Learning, Feature Engineering, Machine Learning Algorithms

    Advanced · Course · 1 - 4 Weeks

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

    Whizlabs

    Azure ML: Designing and Preparing Machine Learning Solutions

    Skills you'll gain: Model Deployment, Machine Learning Algorithms, Machine Learning Methods, Data Management, Model Training, Data Import/Export, Data Pipelines, Development Environment, Statistical Modeling

    Intermediate · Course · 1 - 4 Weeks

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

    Whizlabs

    Azure AI & ML: Optimize Language Models for AI Applications

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Optimization, Microsoft Azure, Prompt Engineering, Model Training, Cloud Deployment, Retrieval-Augmented Generation, Prompt Patterns, Prompt Engineering Tools, Model Evaluation, AI Workflows, Data Pipelines, Fine-tuning, Continuous Monitoring, Data Preprocessing

    Intermediate · Course · 1 - 4 Weeks

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

    IBM

    IBM Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Autoencoders, Feature Engineering, Dimensionality Reduction, Supervised Learning, Generative AI, Classification Algorithms, Regression Analysis, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Science, Machine Learning, Python Programming

    ★ 4.6 (3.6K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • U

    University of Washington

    Machine Learning

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Machine Learning, Image Analysis, Machine Learning Algorithms, AI Personalization, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Supervised Learning, Bayesian Statistics, Statistical Machine Learning, Model Training, Logistic Regression, Statistical Modeling, Data Mining

    ★ 4.6 (16K) · Intermediate · Specialization · 3 - 6 Months

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

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Data Ethics, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms

    ★ 4.9 (39K) · Beginner · Specialization · 1 - 3 Months

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

    IBM

    IBM Introduction to Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Feature Engineering, Dimensionality Reduction, Supervised Learning, Classification Algorithms, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Machine Learning Methods, Statistical Hypothesis Testing, Model Training, Data Processing, Machine Learning

    ★ 4.6 (3.4K) · Intermediate · Specialization · 3 - 6 Months

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

    IBM

    Machine Learning Introduction for Everyone

    Skills you'll gain: Model Evaluation, Predictive Modeling, Model Training, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    ★ 4.6 (309) · Beginner · Course · 1 - 4 Weeks

    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Model Training, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Machine Learning Software, Dimensionality Reduction, Machine Learning, Predictive Modeling, Data Wrangling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting

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

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

    Dartmouth College

    Machine Learning Fundamentals

    Skills you'll gain: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Statistical Machine Learning, Machine Learning Methods, Applied Machine Learning, Machine Learning, Generative Model Architectures, Machine Learning Algorithms, Classification Algorithms, Model Optimization, Regression Analysis, Probability & Statistics

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • I

    IBM

    Machine Learning with Python

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Machine Learning Algorithms, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Model Optimization, Predictive Analytics, Classification Algorithms

    ★ 4.7 (18K) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1…91011…834

In summary, here are 10 of our most popular machine learning model lifecycle courses

  • Fundamentals of Machine Learning: Whizlabs
  • Azure ML: Deploying, Managing, and Experimenting with Models: Whizlabs
  • Azure ML: Designing and Preparing Machine Learning Solutions: Whizlabs
  • Azure AI & ML: Optimize Language Models for AI Applications: Whizlabs
  • IBM Machine Learning: IBM
  • Machine Learning: University of Washington
  • Machine Learning: DeepLearning.AI
  • IBM Introduction to Machine Learning: IBM
  • Machine Learning Introduction for Everyone: IBM
  • Foundations of Machine Learning: Coursera

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