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  • Exponential Random Graph Models

Results for "exponential random graph models"


  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning: Clustering & Retrieval

    Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Statistical Inference, Text Mining, Machine Learning Methods, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Distributed Computing, Probability Distribution, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.4K reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Sequence Models

    Skills you'll gain: Recurrent Neural Networks (RNNs), Hugging Face, Natural Language Processing, Generative AI, Artificial Neural Networks, Embeddings, Large Language Modeling, Deep Learning, Transfer Learning, Fine-tuning, Data Preprocessing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    31K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Validate LLM Embeddings for Production Use

    Skills you'll gain: Embeddings, Model Deployment, MLOps (Machine Learning Operations), Model Evaluation, Data Cleansing, Anomaly Detection, Vector Databases, LLM Application, System Monitoring, Verification And Validation, Data Quality, Legal Technology, Semantic Web, Large Language Modeling, Data Validation, Continuous Monitoring, Performance Testing, Data Manipulation, Dimensionality Reduction, Cost Reduction

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera

    Building an Ecosystem model with Insight Maker

    Skills you'll gain: Simulations, Simulation and Simulation Software, Systems Thinking, Data Sharing, Environmental Science, Mathematical Modeling, Interactive Data Visualization, Biology, Storytelling, Life Sciences

    4.7
    Rating, 4.7 out of 5 stars
    ·
    209 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    D

    DeepLearning.AI

    Knowledge Graphs for RAG

    Skills you'll gain: Retrieval-Augmented Generation, LLM Application, LangChain, Large Language Modeling, Embeddings, Prompt Engineering, Query Languages, Vector Databases, Data Storage, Unstructured Data, Graph Theory

    4.8
    Rating, 4.8 out of 5 stars
    ·
    98 reviews

    Intermediate · Project · Less Than 2 Hours

  • C

    Coursera

    ML Parameters Optimization: GridSearch, Bayesian, Random

    Skills you'll gain: Model Optimization, Model Evaluation, Scikit Learn (Machine Learning Library), Regression Analysis, Fine-tuning, Applied Machine Learning, Machine Learning, Data Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    8 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Using probability distributions for real world problems in R

    Skills you'll gain: Statistical Inference, Probability Distribution, R Programming, Statistical Visualization, R (Software), Statistical Programming, Statistical Methods, Probability & Statistics, Statistics, Data Visualization, Statistical Analysis, Plot (Graphics), 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
    C

    Coursera

    Engineer AI Models: Explain, Tune & Experiment

    Skills you'll gain: Feature Engineering, Fraud detection, Jupyter, Program Management, Model Optimization, Responsible AI, Model Evaluation, Project Management, Performance Improvement, AI literacy, Risk Modeling, Performance Metric, Credit Risk, Performance Analysis, Performance Tuning, Machine Learning Methods, Test Planning, Test Engineering, Applied Machine Learning, Research Design

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Building Statistical Models in R: Linear Regression

    Skills you'll gain: Exploratory Data Analysis, Statistical Modeling, Regression Analysis, Data Visualization, Model Evaluation, Data Analysis, Statistical Methods, Scatter Plots, Statistical Software, R Programming, Statistical Analysis, Plot (Graphics), R (Software), Ggplot2, Statistical Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    20 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Engineering Genetic Circuits: Modeling and Analysis

    Skills you'll gain: Biological Engineering, Bioinformatics, Simulation and Simulation Software, Mathematical Modeling, Mathematical Software, Biotechnology, Simulations, Process Modeling, Differential Equations, Biochemistry, Numerical Analysis, Molecular, Cellular, and Microbiology, Algorithms

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    MLOps in R: Deploying machine learning models using vetiver

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Evaluation, Continuous Deployment, Model Training, Application Deployment, Tidyverse (R Package), R Programming, Health Informatics, Applied Machine Learning, Continuous Monitoring, Predictive Modeling, Machine Learning Methods, Dashboard Creation, Docker (Software), Containerization, Application Programming Interface (API)

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    P

    Packt

    Modern Graph Theory Algorithms with Python

    Skills you'll gain: Graph Theory, Network Analysis, Network Model, Social Network Analysis, NoSQL, Data Store, Data Science, Query Languages, Visualization (Computer Graphics), Data Transformation, Big Data, Machine Learning Methods, Python Programming, Spatial Data Analysis, Deep Learning, Machine Learning, Machine Learning Algorithms, Quantum computing

    Intermediate · Course · 3 - 6 Months

1…789…304

In summary, here are 10 of our most popular exponential random graph models courses

  • Machine Learning: Clustering & Retrieval: University of Washington
  • Sequence Models: DeepLearning.AI
  • Validate LLM Embeddings for Production Use: Coursera
  • Building an Ecosystem model with Insight Maker: Coursera
  • Knowledge Graphs for RAG: DeepLearning.AI
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • Using probability distributions for real world problems in R: Coursera
  • Engineer AI Models: Explain, Tune & Experiment: Coursera
  • Building Statistical Models in R: Linear Regression: Coursera
  • Engineering Genetic Circuits: Modeling and Analysis: University of Colorado Boulder

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