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  • Exponential Random Graph Models

Results for "exponential random graph models"


  • 2

    28DIGITAL

    Quantitative Model Checking

    Skills you'll gain: Computational Logic, Markov Model, Verification And Validation, Theoretical Computer Science, Mathematical Modeling, Systems Analysis, Process Modeling, Probability, Algorithms, Probability Distribution, Logical Reasoning

    4.3
    Rating, 4.3 out of 5 stars
    ·
    54 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Exploratory Data Analysis & Core ML Algorithms

    Skills you'll gain: Exploratory Data Analysis, Model Optimization, Model Training, Applied Machine Learning, Predictive Modeling, Decision Tree Learning, Data Analysis, Regression Analysis, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Data Wrangling, Model Evaluation, Data Preprocessing, Statistical Machine Learning, Feature Engineering

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Advanced PyTorch Techniques and Applications

    Skills you'll gain: PyTorch (Machine Learning Library), Natural Language Processing, Generative Adversarial Networks (GANs), Vision Transformer (ViT), Deep Learning, Generative Model Architectures, Graph Theory, Dimensionality Reduction, Network Model, Unsupervised Learning, Model Optimization, Embeddings, Artificial Neural Networks, Machine Learning Methods, Supervised Learning, Model Evaluation, Model Training, Model Deployment, Flask (Web Framework)

    4.5
    Rating, 4.5 out of 5 stars
    ·
    27 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    W

    Whizlabs

    AWS: Model Training , Optimization & Deployment

    Skills you'll gain: Model Optimization, Model Training, Model Deployment, Cloud Deployment, Amazon Elastic Compute Cloud, Model Evaluation, Classification Algorithms, Continuous Deployment, Continuous Integration, Predictive Modeling, Debugging

    Intermediate · 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 Methods, Combinatorics, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Bayesian Statistics, Data Science, Simulations

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    D

    DeepLearning.AI

    Generative AI with Large Language Models

    Skills you'll gain: Generative AI, Large Language Modeling, Generative Model Architectures, Fine-tuning, LLM Application, Model Training, Model Deployment, Python Programming, Scalability, Model Optimization, Machine Learning, Model Evaluation, Reinforcement Learning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    3.6K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Neural Networks and Random Forests

    Skills you'll gain: Model Evaluation, Random Forest Algorithm, Model Optimization, Keras (Neural Network Library), Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Decision Tree Learning, Machine Learning Methods, Applied Machine Learning, Predictive Modeling, Fine-tuning, Scikit Learn (Machine Learning Library), Regression Analysis, Classification Algorithms, Python Programming

    3.3
    Rating, 3.3 out of 5 stars
    ·
    17 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    E

    EDUCBA

    Python: Implement & Evaluate Random Forests for ML

    Skills you'll gain: Model Evaluation, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Applied Machine Learning, Model Optimization, Model Training, Data Processing, Machine Learning Methods, Decision Tree Learning, Machine Learning Algorithms, Classification Algorithms, Analysis, Python Programming

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Test-Driven Development Project: Random Person Generator

    Skills you'll gain: Unit Testing, Test Driven Development (TDD), Program Development, Mockups, Test Script Development, Development Testing, Software Testing, Test Case

    4.4
    Rating, 4.4 out of 5 stars
    ·
    9 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    D

    DeepLearning.AI

    Finetuning Large Language Models

    Skills you'll gain: Fine-tuning, Large Language Modeling, Model Training, Prompt Engineering, Retrieval-Augmented Generation, Model Optimization, Transfer Learning, Data Preprocessing

    4.6
    Rating, 4.6 out of 5 stars
    ·
    618 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Graph Search, Shortest Paths, and Data Structures

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Social Network Analysis, Network Analysis, Theoretical Computer Science, Probability & Statistics

    4.8
    Rating, 4.8 out of 5 stars
    ·
    2K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Honors Algebra 2: Algebraic, Exponential & Log Functions

    Skills you'll gain: Algebra, Applied Mathematics, Graphing, Mathematical Modeling, Advanced Mathematics, Calculus, Predictive Modeling

    Beginner · Course · 1 - 4 Weeks

1…91011…304

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

  • Quantitative Model Checking: 28DIGITAL
  • Exploratory Data Analysis & Core ML Algorithms: Packt
  • Advanced PyTorch Techniques and Applications: Packt
  • AWS: Model Training , Optimization & Deployment: Whizlabs
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Generative AI with Large Language Models: DeepLearning.AI
  • Neural Networks and Random Forests: LearnQuest
  • Python: Implement & Evaluate Random Forests for ML: EDUCBA
  • Test-Driven Development Project: Random Person Generator: LearnQuest
  • Finetuning Large Language Models: DeepLearning.AI

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