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  • Gibbs Sampling

Results for "gibbs sampling"


  • C

    Coursera

    Data Balancing with Gen AI: Credit Card Fraud Detection

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Fraud detection, Keras (Neural Network Library), Tensorflow, Data Preprocessing, Deep Learning, Dimensionality Reduction, Exploratory Data Analysis, Anomaly Detection, Data Visualization, Data Synthesis, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
    ·
    9 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Introduction to Genomic Technologies

    Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Computer Science, Statistical Analysis, Computational Thinking, Biostatistics, Statistics, Software Engineering, Algorithms, Biology

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.8K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Statistics and Calculus Methods for Data Analysis

    Skills you'll gain: Statistical Analysis, Statistical Modeling, Predictive Modeling, Data Analysis, Statistics, Integral Calculus, Probability & Statistics, Data Science, Probability Distribution, Calculus, Mathematics and Mathematical Modeling, Applied Mathematics, Derivatives, Mathematical Modeling, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Python for Genomic Data Science

    Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Object Oriented Programming (OOP), File I/O, Computational Logic, Package and Software Management, Data Manipulation

    4.3
    Rating, 4.3 out of 5 stars
    ·
    1.8K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Simulations

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Using probability distributions for real world problems in R

    Skills you'll gain: Statistical Inference, Probability Distribution, R Programming, Statistical Visualization, Statistics, Data Visualization, Statistical Analysis, Statistical Modeling, Statistical Hypothesis Testing, Data Analysis, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    37 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    D

    Dartmouth College

    Foundations for Machine Learning

    Skills you'll gain: Classification Algorithms

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    C

    Case Western Reserve University

    Basic Principles of Geostatistical Geospatial Modeling

    Skills you'll gain: Geostatistics, Exploratory Data Analysis, Spatial Data Analysis, Spatial Analysis, Geospatial Mapping, Geospatial Information and Technology, Statistical Modeling, R Programming, Statistical Analysis, Probability & Statistics, Data Analysis, Data-Driven Decision-Making, Regression Analysis, Correlation Analysis, Data Validation, Histogram, Box Plots, Simulation and Simulation Software, Model Evaluation

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Exploratory Data Analysis

    Skills you'll gain: Exploratory Data Analysis, Plot (Graphics), Statistical Visualization, Ggplot2, Dimensionality Reduction, Data Visualization Software, R Programming, Graphing, Data Analysis, Statistical Analysis, Unsupervised Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    6.1K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
    Preview
    N

    Northeastern University

    Statistical Learning for Engineering Part 1

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Logistic Regression, Unstructured Data, Model Evaluation, Dimensionality Reduction

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Getting and Cleaning Data

    Skills you'll gain: Data Manipulation, Data Cleansing, Data Integration, Data Preprocessing, Data Import/Export, Data Collection, Data Management, Web Scraping, Data Access, R Programming, MySQL, Application Programming Interface (API)

    4.5
    Rating, 4.5 out of 5 stars
    ·
    8.1K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Importing Data in the Tidyverse

    Skills you'll gain: Data Import/Export, Web Scraping, Tidyverse (R Package), Data Integration, Data Manipulation, Data Transformation, Relational Databases, Google Sheets, Unstructured Data, R Programming, Extensible Markup Language (XML), Spreadsheet Software, Databases, SQL, Application Programming Interface (API)

    4.7
    Rating, 4.7 out of 5 stars
    ·
    51 reviews

    Beginner · Course · 1 - 3 Months

1…272829…30

In summary, here are 10 of our most popular gibbs sampling courses

  • Data Balancing with Gen AI: Credit Card Fraud Detection: Coursera
  • Introduction to Genomic Technologies: Johns Hopkins University
  • Statistics and Calculus Methods for Data Analysis: University of Pittsburgh
  • Python for Genomic Data Science: Johns Hopkins University
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Using probability distributions for real world problems in R: Coursera
  • Foundations for Machine Learning: Dartmouth College
  • Basic Principles of Geostatistical Geospatial Modeling: Case Western Reserve University
  • Exploratory Data Analysis: Johns Hopkins University
  • Statistical Learning for Engineering Part 1: Northeastern University

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