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  • Understanding Purpose Of Sequential Probabilistic Inference Steps


Results for "understanding+purpose+of+sequential-probabilistic-inference+steps"


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    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.1K reviews

    Intermediate · Specialization · 1 - 3 Months

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    Stanford University

    Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Programming Principles, Social Network Analysis, Network Analysis, Computational Thinking, Analysis, Computer Science, Network Routing, Probability, Pseudocode, Computational Logic, Operations Research

    4.8
    Rating, 4.8 out of 5 stars
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    6K reviews

    Intermediate · Specialization · 3 - 6 Months

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    University of California, Santa Cruz

    Bayesian Statistics: From Concept to Data Analysis

    Skills you'll gain: Bayesian Statistics, Statistical Inference, Statistical Methods, Probability & Statistics, Statistics, Statistical Modeling, Probability, Probability Distribution, Data Analysis, R Programming, Regression Analysis, R (Software), Microsoft Excel, Analytical Skills, Statistical Visualization, Predictive Modeling, Data Visualization, Data Modeling

    4.6
    Rating, 4.6 out of 5 stars
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    3.2K reviews

    Intermediate · Course · 1 - 4 Weeks

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    University of California San Diego

    Combinatorics and Probability

    Skills you'll gain: Combinatorics, Probability, Probability Distribution, Algorithms, Bayesian Statistics, Mathematical Modeling, Statistics, Arithmetic, Python Programming, Simulations

    4.6
    Rating, 4.6 out of 5 stars
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    866 reviews

    Beginner · Course · 1 - 3 Months

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    Northeastern University

    Foundations of Statistical Learning & Algorithms

    Skills you'll gain: Model Evaluation, Linear Algebra, Statistical Machine Learning, Probability, Bayesian Statistics, Probability Distribution, Mathematical Modeling, Machine Learning, Applied Mathematics, Statistical Inference, Dimensionality Reduction, Algebra

    Mixed · Course · 1 - 4 Weeks

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    University of Colorado Boulder

    Algorithms for Battery Management Systems

    Skills you'll gain: Electrical Safety, Electrical Systems, High Voltage, Simulations, Electronic Components, Safety Standards, Estimation, Control Systems, Basic Electrical Systems, Thermal Management, Mathematical Modeling, Power Electronics, Electrical Power, Failure Analysis, Probability, Electrical Engineering, Energy and Utilities, Model Evaluation, Simulation and Simulation Software, Machine Learning Methods

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    4.7
    Rating, 4.7 out of 5 stars
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    2.6K reviews

    Intermediate · Specialization · 3 - 6 Months

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    DeepLearning.AI

    Natural Language Processing with Probabilistic Models

    Skills you'll gain: Natural Language Processing, Markov Model, Embeddings, Text Mining, Data Preprocessing, Artificial Neural Networks, Machine Learning Methods, Algorithms, Statistical Modeling, Probability & Statistics

    4.7
    Rating, 4.7 out of 5 stars
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    1.8K reviews

    Intermediate · Course · 1 - 4 Weeks

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    U

    University of Pennsylvania

    Statistics for Data Science Essentials

    Skills you'll gain: Probability, Probability & Statistics, Sampling (Statistics), Probability Distribution, Statistics, Data Science, Statistical Inference, Descriptive Statistics, Statistical Analysis, General Mathematics

    4.4
    Rating, 4.4 out of 5 stars
    ·
    10 reviews

    Intermediate · Course · 1 - 4 Weeks

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    I

    Imperial College London

    Probabilistic Deep Learning with TensorFlow 2

    Skills you'll gain: Tensorflow, Autoencoders, Generative Model Architectures, Deep Learning, Applied Machine Learning, Image Analysis, Bayesian Statistics, Probability Distribution, Unsupervised Learning, Sampling (Statistics)

    4.7
    Rating, 4.7 out of 5 stars
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    109 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
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    Alberta Machine Intelligence Institute

    Introduction to Generative AI: Concepts and Techniques

    Skills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, Generative AI, Generative Model Architectures, Large Language Modeling, ChatGPT, OpenAI API, Open Source Technology, Responsible AI, Embeddings, Artificial Intelligence, Data Ethics, Natural Language Processing, Information Privacy

    Mixed · Course · 1 - 4 Weeks

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    Illinois Tech

    Bayesian Computational Statistics

    Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Inference, Regression Analysis, Statistical Analysis, Statistical Modeling, Statistical Programming, Sampling (Statistics), R Programming, Markov Model, Logistic Regression, Probability, Simulations, Model Evaluation, Probability Distribution

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    Intermediate · Course · 1 - 3 Months

  • Status: Preview
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    U

    Universidad Nacional Autónoma de México

    Estadística y probabilidad: principios de Inferencia

    Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability Distribution, Sampling (Statistics), Probability & Statistics, Probability, Statistics, Statistical Analysis, Descriptive Statistics

    3.1
    Rating, 3.1 out of 5 stars
    ·
    16 reviews

    Beginner · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular understanding+purpose+of+sequential-probabilistic-inference+steps courses

  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Algorithms: Stanford University
  • Bayesian Statistics: From Concept to Data Analysis: University of California, Santa Cruz
  • Combinatorics and Probability: University of California San Diego
  • Foundations of Statistical Learning & Algorithms: Northeastern University
  • Algorithms for Battery Management Systems: University of Colorado Boulder
  • Natural Language Processing with Probabilistic Models: DeepLearning.AI
  • Statistics for Data Science Essentials: University of Pennsylvania
  • Probabilistic Deep Learning with TensorFlow 2: Imperial College London
  • Introduction to Generative AI: Concepts and Techniques: Alberta Machine Intelligence Institute

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