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  • Probabilistic Neural Network

Results for "probabilistic neural network"


  • Status: New
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    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, Statistical Programming, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Probability & Statistics, Dimensionality Reduction

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Neural Networks and Random Forests

    Skills you'll gain: Random Forest Algorithm, Keras (Neural Network Library), Classification And Regression Tree (CART), Tensorflow, Deep Learning, Artificial Neural Networks, Predictive Modeling, Scikit Learn (Machine Learning Library), Supervised Learning, Machine Learning, Regression Analysis, Python Programming

    2.9
    Rating, 2.9 out of 5 stars
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    13 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Stanford University

    Probabilistic Graphical Models 1: Representation

    Skills you'll gain: Bayesian Network, Graph Theory, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis, Natural Language Processing

    4.6
    Rating, 4.6 out of 5 stars
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    1.4K reviews

    Advanced · Course · 1 - 3 Months

  • Status: Preview
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    Sungkyunkwan University

    Fundamentals of CNNs and RNNs

    Skills you'll gain: Image Analysis, Computer Vision, Artificial Neural Networks, Natural Language Processing, Deep Learning, Network Architecture, Network Model, Machine Learning

    4.4
    Rating, 4.4 out of 5 stars
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    39 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    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), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

    4.6
    Rating, 4.6 out of 5 stars
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    647 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Stanford University

    Probabilistic Graphical Models 2: Inference

    Skills you'll gain: Bayesian Network, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Machine Learning Algorithms, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
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    488 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
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    P

    Packt

    Modern Natural Language Processing

    Skills you'll gain: Natural Language Processing, Deep Learning, Large Language Modeling, Text Mining, Semantic Web, Generative AI, PyTorch (Machine Learning Library), Artificial Neural Networks, Python Programming, Cryptography, Generative Model Architectures, Applied Machine Learning, Machine Learning Methods, Unsupervised Learning, Probability Distribution, Machine Learning Algorithms, Algorithms

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    Johns Hopkins University

    Introduction to Neural Networks

    Skills you'll gain: Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Applied Machine Learning, Image Analysis, Machine Learning, Computer Vision, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Network Architecture, Algorithms, Statistical Methods, Performance Tuning, Linear Algebra

    4.3
    Rating, 4.3 out of 5 stars
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    6 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Databricks

    Introduction to Computational Statistics for Data Scientists

    Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Classification And Regression Tree (CART), Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Probability Distribution, Data Science, Markov Model, Statistics, Simulations, Python Programming, Statistical Visualization, Mathematical Software, Statistical Inference

    4
    Rating, 4 out of 5 stars
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    109 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Preview
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    Northeastern University

    Foundations of Statistical Learning & Algorithms

    Skills you'll gain: Linear Algebra, Statistical Machine Learning, Mathematics and Mathematical Modeling, Statistical Modeling, Probability, Probability & Statistics, Statistical Methods, Bayesian Statistics, Probability Distribution, Mathematical Modeling, General Mathematics, Machine Learning, Applied Mathematics, Statistical Inference, Algebra

    Mixed · Course · 1 - 4 Weeks

  • P

    Packt

    Deep Neural Network for Beginners Using Python

    Skills you'll gain: Deep Learning, Data Processing, Artificial Neural Networks, Feature Engineering, Python Programming, Network Architecture, Machine Learning Algorithms, NumPy, Pandas (Python Package), Regression Analysis, Supervised Learning, Performance Tuning

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models 3: Learning

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Unstructured Data, Statistical Methods, Probability & Statistics, Algorithms, Test Data

    4.6
    Rating, 4.6 out of 5 stars
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    303 reviews

    Advanced · Course · 1 - 3 Months

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In summary, here are 10 of our most popular probabilistic neural network courses

  • Statistical Learning for Engineering Part 1: Northeastern University
  • Neural Networks and Random Forests: LearnQuest
  • Probabilistic Graphical Models 1: Representation: Stanford University
  • Fundamentals of CNNs and RNNs: Sungkyunkwan University
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Modern Natural Language Processing: Packt
  • Introduction to Neural Networks: Johns Hopkins University
  • Introduction to Computational Statistics for Data Scientists: Databricks
  • Foundations of Statistical Learning & Algorithms: Northeastern University

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