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  • Distributional Semantics


Results for "distributional semantics"


  • Status: Free Trial
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    U

    University of California, Santa Cruz

    Coding for Everyone: C and C++

    Skills you'll gain: C++ (Programming Language), Object Oriented Programming (OOP), Programming Principles, Software Design Patterns, Computer Programming, Algorithms, C (Programming Language), Graph Theory, Debugging, Artificial Intelligence, Data Structures, Game Design, Software Documentation

    4.5
    Rating, 4.5 out of 5 stars
    ·
    9.6K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
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    D

    DeepLearning.AI

    Natural Language Processing

    Skills you'll gain: Natural Language Processing, Supervised Learning, Transfer Learning, Recurrent Neural Networks (RNNs), Markov Model, Embeddings, Text Mining, Dimensionality Reduction, Machine Learning Methods, Statistical Machine Learning, Artificial Neural Networks, Classification Algorithms, Data Preprocessing, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Feature Engineering, Applied Machine Learning, Algorithms, Keras (Neural Network Library)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    6.2K reviews

    Intermediate · Specialization · 3 - 6 Months

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    S

    Stanford University

    Probabilistic Graphical Models

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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

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    U

    University of Colorado Boulder

    Foundations of Probability and Statistics

    Skills you'll gain: Probability, Statistical Inference, Estimation, Statistical Methods, Probability & Statistics, Statistics, Probability Distribution, Markov Model, Data Literacy, Statistical Analysis, Sampling (Statistics), Bayesian Statistics, Applied Mathematics, Artificial Intelligence, Generative AI, Data Science, Theoretical Computer Science, Data Analysis, Machine Learning Algorithms, Mathematical Theory & Analysis

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    4.4
    Rating, 4.4 out of 5 stars
    ·
    344 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    U

    University of California, Santa Cruz

    C and Go: Classical and Modern Programming

    Skills you'll gain: Go (Programming Language), File I/O, Data Structures, Programming Principles, Object Oriented Programming (OOP), Debugging, Computer Programming, Unit Testing, C (Programming Language), Program Development, Integrated Development Environments, Computer Science, Software Testing, Algorithms, Integration Testing, Software Design, System Design and Implementation, Distributed Computing, Software Documentation

    4.5
    Rating, 4.5 out of 5 stars
    ·
    7.3K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    I

    IBM

    Generative AI Language Modeling with Transformers

    Skills you'll gain: Generative AI, Large Language Modeling, PyTorch (Machine Learning Library), Transfer Learning, Embeddings, Natural Language Processing, Text Mining, Applied Machine Learning, Performance Tuning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    140 reviews

    Intermediate · Course · 1 - 4 Weeks

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    P

    Packt

    Complete Modern C++ (C++11/14/17)

    Skills you'll gain: C and C++, C++ (Programming Language), Object Oriented Programming (OOP), File I/O, Computer Programming, Microsoft Visual Studio, System Programming, Apple Xcode, Development Environment, Algorithms, File Systems, Software Design Patterns, Data Structures, Performance Tuning, Debugging, File Management

    4.4
    Rating, 4.4 out of 5 stars
    ·
    27 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
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    A

    Arizona State University

    Probability, Statistical Inference and Regression Analysis

    Skills you'll gain: Probability & Statistics, Analytical Skills, Exploratory Data Analysis, Estimation, Logistic Regression

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    Microsoft

    Working with large language models using Azure

    Skills you'll gain: Generative Model Architectures, ChatGPT, AI Security, Semantic Web, Vector Databases

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    U

    University of Michigan

    Programming for Everybody (Getting Started with Python)

    Skills you'll gain: Debugging, Programming Principles, Computer Programming, Python Programming, Integrated Development Environments, Computer Programming Tools, Computational Thinking, Software Installation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    233K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
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    A

    Arizona State University

    Bayesian Statistical Concepts and Methods

    Skills you'll gain: Bayesian Statistics, Statistical Modeling, Bayesian Network, Statistical Methods, Statistical Analysis, Data Analysis, R Programming, Data-Driven Decision-Making, Statistical Inference, Markov Model, Simulations, Probability Distribution

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    I

    IBM

    Gen AI Foundational Models for NLP & Language Understanding

    Skills you'll gain: PyTorch (Machine Learning Library), Large Language Modeling, Embeddings, Generative AI, Natural Language Processing, Transfer Learning, Recurrent Neural Networks (RNNs), Data Ethics, Artificial Neural Networks, Classification Algorithms, Model Evaluation, Data Preprocessing, Feature Engineering

    4.4
    Rating, 4.4 out of 5 stars
    ·
    183 reviews

    Intermediate · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular distributional semantics courses

  • Coding for Everyone: C and C++: University of California, Santa Cruz
  • Natural Language Processing: DeepLearning.AI
  • Probabilistic Graphical Models: Stanford University
  • Foundations of Probability and Statistics: University of Colorado Boulder
  • C and Go: Classical and Modern Programming: University of California, Santa Cruz
  • Generative AI Language Modeling with Transformers: IBM
  • Complete Modern C++ (C++11/14/17): Packt
  • Probability, Statistical Inference and Regression Analysis: Arizona State University
  • Working with large language models using Azure: Microsoft
  • Programming for Everybody (Getting Started with Python): University of Michigan

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