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  • Bayesian Methods For Machine Learning

Results for "bayesian methods for machine learning"


  • Status: Free Trial
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    U

    University of Colorado Boulder

    Teacher SEL: Programs, Possibilities, and Contexts

    Skills you'll gain: Mindfulness, Teaching, Self-Awareness, Classroom Management, Empathy & Emotional Intelligence, Social Studies, Storytelling, Adult Education, Parent Communication, Resilience, Cultural Responsiveness, Stress Management, Emotional Intelligence, Community Development, Collaboration, Liberal Arts

    4.7
    Rating, 4.7 out of 5 stars
    ·
    155 reviews

    Advanced · Course · 1 - 4 Weeks

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    S

    Simplilearn

    Introduction Course to Autoencoders, VAEs, and GANs

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Autoencoders, Deep Learning, Convolutional Neural Networks, Tensorflow, Unsupervised Learning, Dimensionality Reduction, Model Evaluation

    Beginner · Course · 1 - 4 Weeks

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    C

    Coursera

    Use Canva to Create an Interactive Mind Map

    Skills you'll gain: Canva (Software), Multimedia, Interactive Data Visualization, Data Visualization, Marketing Design, Data Sharing, Presentations, Design, Color Theory, Graphic Design, Marketing, Communication

    4.7
    Rating, 4.7 out of 5 stars
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    437 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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    J

    Johns Hopkins University

    Leadership: An Introduction

    Skills you'll gain: Persuasive Communication, Business Ethics, Creativity, Creative Thinking, Leadership, Organizational Leadership, Ethical Standards And Conduct, Influencing, Innovation, Diversity and Inclusion, Team Leadership, Strategic Leadership, Business Leadership, Leadership Development, Leadership and Management, Responsible AI, Communication, Artificial Intelligence, Decision Making, Cultural Diversity

    4.5
    Rating, 4.5 out of 5 stars
    ·
    39 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    U

    University of California, Davis

    Hands-on Data Centric Visual AI

    Skills you'll gain: Data Quality, Data Cleansing, Computer Vision, Visualization (Computer Graphics), Data Preprocessing, Deep Learning, Image Analysis, Convolutional Neural Networks, Model Evaluation, Data Manipulation, Applied Machine Learning, Data Analysis

    Intermediate · Course · 1 - 4 Weeks

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    E

    Emory University

    Consulting Tools and Tips

    Skills you'll gain: Consulting, Management Consulting, Business Consulting, Benchmarking, Microsoft Excel, Business Research, Analysis, Market Research, Competitive Analysis, Market Analysis, Data Modeling, Supply Chain, Interviewing Skills, Trend Analysis, Business Strategy

    4.9
    Rating, 4.9 out of 5 stars
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    399 reviews

    Beginner · Course · 1 - 3 Months

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    C

    Coursera

    Create an Infographic in Canva

    Skills you'll gain: Infographics, Canva (Software), Graphic and Visual Design, Design Elements And Principles

    4.6
    Rating, 4.6 out of 5 stars
    ·
    201 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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    I

    IBM

    Generative AI: Elevate your Data Engineering Career

    Skills you'll gain: Generative AI, Generative Model Architectures, Database Design, Data Pipelines, Query Languages, Extract, Transform, Load, Snowflake Schema, Star Schema, Responsible AI, Data Warehousing, Prompt Engineering, Data Ethics, Data Infrastructure, Data Architecture, AI Enablement, Data Mining, Data Synthesis, Data Analysis, Artificial Intelligence, Convolutional Neural Networks

    4.7
    Rating, 4.7 out of 5 stars
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    54 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    S

    Sapienza University of Rome

    Paesaggi di Roma Antica. Archeologia e storia del Palatino.

    Skills you'll gain: Ancient History, Scientific Methods, Research, Research Methodologies, Investigation, Spatial Analysis, Art History, Geographic Information Systems, World History, Cultural Responsiveness, Data Integration, Culture, Information Systems

    4.8
    Rating, 4.8 out of 5 stars
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    146 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Computational and Graphical Models in Probability

    Skills you'll gain: Network Analysis, Statistical Modeling, Bayesian Network, R (Software), R Programming, Social Network Analysis, Simulations, Graph Theory, Statistical Analysis, Probability & Statistics, Markov Model, Probability Distribution, Data Visualization, Machine Learning, Statistical Hypothesis Testing

    Intermediate · Course · 1 - 4 Weeks

  • G

    Google Cloud

    Introduction to Computer Vision with TensorFlow

    Skills you'll gain: Model Evaluation, Tensorflow, Convolutional Neural Networks, Computer Vision, Keras (Neural Network Library), Development Environment, Image Analysis, Machine Learning, Deep Learning, Data Persistence, Artificial Neural Networks

    5
    Rating, 5 out of 5 stars
    ·
    7 reviews

    Beginner · Project · Less Than 2 Hours

  • C

    Coursera

    Create a Storyboard using Canva

    Skills you'll gain: Storyboarding, Storytelling, Canva (Software), Graphical Tools, Animations, Content Creation, Graphic Design, Design and Product, Business, Marketing

    4.6
    Rating, 4.6 out of 5 stars
    ·
    206 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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In summary, here are 10 of our most popular bayesian methods for machine learning courses

  • Teacher SEL: Programs, Possibilities, and Contexts: University of Colorado Boulder
  • Introduction Course to Autoencoders, VAEs, and GANs: Simplilearn
  • Use Canva to Create an Interactive Mind Map: Coursera
  • Leadership: An Introduction: Johns Hopkins University
  • Hands-on Data Centric Visual AI: University of California, Davis
  • Consulting Tools and Tips: Emory University
  • Create an Infographic in Canva: Coursera
  • Generative AI: Elevate your Data Engineering Career : IBM
  • Paesaggi di Roma Antica. Archeologia e storia del Palatino.: Sapienza University of Rome
  • Computational and Graphical Models in Probability: Johns Hopkins University

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