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  • Variational Bayesian Methods

Results for "variational+bayesian+methods"


  • S

    Simplilearn

    Introduction Course to Autoencoders, VAEs, and GANs

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

    Beginner · Course · 1 - 4 Weeks

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

    University of Minnesota

    Optimization for Decision Making

    Skills you'll gain: Operations Research, Mathematical Modeling, Business Modeling, Business Analytics, Analytics, Process Optimization, Data-Driven Decision-Making, Model Optimization, Microsoft Excel, Decision Making, Excel Formulas, Spreadsheet Software, Graphing

    ★ 4.7 (90) · Beginner · Course · 1 - 4 Weeks

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

    University of Michigan

    The Finite Element Method for Problems in Physics

    Skills you'll gain: Finite Element Methods, Engineering Analysis, Mathematical Software, Numerical Analysis, Mathematical Modeling, C++ (Programming Language), Structural Engineering, Computer Programming

    ★ 4.6 (564) · Intermediate · Course · 3 - 6 Months

    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • I

    Imperial College London

    Mathematics for Machine Learning: Multivariate Calculus

    Skills you'll gain: Regression Analysis, Calculus, Model Optimization, Mathematical Software, Numerical Analysis, Applied Mathematics, Applied Machine Learning, Linear Algebra, Artificial Neural Networks, Derivatives

    ★ 4.7 (5.8K) · Beginner · Course · 1 - 3 Months

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

    University of California, Santa Cruz

    Bayesian Statistics: Mixture Models

    Skills you'll gain: R Programming, Statistical Programming, Statistical Modeling, Bayesian Statistics, Statistical Software, Markov Model, Statistical Methods, Probability & Statistics, Statistical Inference, Sampling (Statistics), Probability Distribution, Numerical Analysis, Classification Algorithms

    ★ 4.5 (63) · Intermediate · Course · 1 - 3 Months

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

    University of Alberta

    Sample-based Learning Methods

    Skills you'll gain: Reinforcement Learning, Machine Learning Methods, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Applied Machine Learning, Probability Distribution

    ★ 4.8 (1.3K) · Intermediate · Course · 1 - 3 Months

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

    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Probability, Statistical Inference, Statistics, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Correlation Analysis, Histogram, Statistical Visualization, Box Plots

    ★ 4.6 (685) · Intermediate · Course · 1 - 4 Weeks

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

    Johns Hopkins University

    Advanced Probability and Statistical Methods

    Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Probability & Statistics, Statistical Methods, Statistical Programming, Probability Distribution, Data Analysis, Statistical Software, Markov Model, Data Science, Statistical Modeling, Statistical Inference, Probability, Correlation Analysis, R Programming

    Intermediate · Course · 1 - 3 Months

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

    Imperial College London

    Probabilistic Deep Learning with TensorFlow 2

    Skills you'll gain: Generative AI, Tensorflow, Autoencoders, Generative Model Architectures, Bayesian Network, Deep Learning, Image Analysis, Bayesian Statistics, Model Optimization, Probability Distribution, Model Training, Sampling (Statistics), Data Transformation

    ★ 4.7 (109) · Advanced · Course · 1 - 3 Months

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

    University of Toronto

    Bioinformatic Methods I

    Skills you'll gain: Life Sciences, Data Analysis, Microbiology, Analysis

    ★ 4.7 (1.8K) · Beginner · Course · 1 - 3 Months

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

    Johns Hopkins University

    Calculus through Data & Modelling: Techniques of Integration

    Skills you'll gain: Integral Calculus, Numerical Analysis, Calculus, Probability, Applied Mathematics, Advanced Mathematics, Estimation, Probability & Statistics, Geometry, Mathematical Modeling, Graphing

    ★ 4.7 (54) · Intermediate · Course · 1 - 4 Weeks

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

    Ludwig-Maximilians-Universität München (LMU)

    Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Integral Calculus, Simulation and Simulation Software, Python Programming, Mechanics, Simulations, Derivatives

    ★ 4.8 (391) · Intermediate · Course · 1 - 3 Months

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

In summary, here are 10 of our most popular variational+bayesian+methods courses

  • Introduction Course to Autoencoders, VAEs, and GANs: Simplilearn
  • Optimization for Decision Making: University of Minnesota
  • The Finite Element Method for Problems in Physics: University of Michigan
  • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
  • Bayesian Statistics: Mixture Models: University of California, Santa Cruz
  • Sample-based Learning Methods: University of Alberta
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Advanced Probability and Statistical Methods: Johns Hopkins University
  • Probabilistic Deep Learning with TensorFlow 2: Imperial College London
  • Bioinformatic Methods I: University of Toronto

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