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Results for "distributional semantics"
University of California, Irvine
Skills you'll gain: Grammar, Vocabulary, Language Learning
DeepLearning.AI
Skills you'll gain: Natural Language Processing, PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Tensorflow, Machine Learning Methods, Artificial Intelligence, Text Mining, Data Processing
Stanford University
Skills you'll gain: Bayesian Network, Graph Theory, Probability Distribution, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis, Applied Machine Learning, Natural Language Processing
DeepLearning.AI
Skills you'll gain: Natural Language Processing, Markov Model, Text Mining, Artificial Intelligence, Artificial Neural Networks, Data Processing, Deep Learning, Algorithms, Computer Programming, Unstructured Data, Machine Learning, Probability & Statistics
Skills you'll gain: Event-Driven Programming, Application Development, Interactive Design, Graphical Tools, User Interface (UI), Programming Principles, Computer Graphics, Python Programming, Program Development, Computer Programming, Simulations, Development Environment, Debugging, Arithmetic
DeepLearning.AI
Skills you'll gain: Natural Language Processing, Keras (Neural Network Library), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Text Mining, Machine Learning
Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Natural Language Processing, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Deep Learning, Jupyter, Data Processing, Machine Learning
Stanford University
Skills you'll gain: Bayesian Network, Statistical Inference, Markov Model, Statistical Machine Learning, Graph Theory, Sampling (Statistics), Applied Machine Learning, Probability & Statistics, Algorithms, Machine Learning Algorithms
Johns Hopkins University
Skills you'll gain: Calculus, Applied Mathematics, Data Modeling, Estimation, Graphing, Mathematical Modeling, Algebra, Trigonometry, Cost Estimation, Engineering Calculations, Linear Algebra, Data Analysis, Plot (Graphics), Advanced Mathematics, Mathematical Theory & Analysis, Derivatives, Geometry
University of Washington
Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Big Data, Statistical Inference, Dimensionality Reduction, Text Mining, Statistical Modeling, Machine Learning Algorithms, Machine Learning, Scalability, Data Structures, Distributed Computing, Probability Distribution, Algorithms
- Status: Free
University of Alberta
Skills you'll gain: Computational Thinking, Programming Principles, Computer Programming, Program Development, Software Quality Assurance, Python Programming, Algorithms, Software Design, Visualization (Computer Graphics), Debugging, Problem Management, Computer Science, Test Planning
Skills you'll gain: Generative AI, ChatGPT, Natural Language Processing, Computer Vision, Deep Learning, Predictive Modeling, Text Mining, Data Ethics, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, Machine Learning, Tensorflow, Supervised Learning, Artificial Neural Networks, Software Development Tools, GitHub, Artificial Intelligence, Python Programming, Information Privacy
In summary, here are 10 of our most popular distributional semantics courses
- Adjectives and Adjective Clauses:Â University of California, Irvine
- Natural Language Processing with Attention Models:Â DeepLearning.AI
- Probabilistic Graphical Models 1: Representation:Â Stanford University
- Natural Language Processing with Probabilistic Models:Â DeepLearning.AI
- An Introduction to Interactive Programming in Python (Part 1):Â Rice University
- Natural Language Processing with Sequence Models:Â DeepLearning.AI
- Generative AI and LLMs: Architecture and Data Preparation:Â IBM
- Probabilistic Graphical Models 2: Inference:Â Stanford University
- Differential Calculus through Data and Modeling:Â Johns Hopkins University
- Machine Learning: Clustering & Retrieval:Â University of Washington