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  • Mathematical Foundations Of Neural Networks


Results for "mathematical+foundations+of+neural+networks"


  • Status: Preview
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    N

    Northeastern University

    Generative AI: Foundations and Concepts

    Skills you'll gain: Generative AI, Generative Model Architectures, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Bayesian Network, Machine Learning Methods, Mathematical Modeling, Estimation, Model Evaluation, Applied Mathematics, Dimensionality Reduction, Network Architecture, Probability & Statistics

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    W

    Whizlabs

    NVIDIA: Fundamentals of NLP and Transformers

    Skills you'll gain: Natural Language Processing, Recurrent Neural Networks (RNNs), Embeddings, Transfer Learning, Data Pipelines, Data Preprocessing, Artificial Neural Networks, Unstructured Data, Machine Learning Methods, Machine Learning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Deep Learning Frameworks and Neural Networks Simplified

    Skills you'll gain: Recurrent Neural Networks (RNNs), Model Deployment, Keras (Neural Network Library), Deep Learning, Tensorflow, Artificial Neural Networks, Convolutional Neural Networks, Application Frameworks, Artificial Intelligence, Machine Learning Methods, Image Analysis, Data Preprocessing

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    I

    IBM

    Deep Learning with Keras and Tensorflow

    Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Convolutional Neural Networks, Unsupervised Learning, Deep Learning, Autoencoders, Tensorflow, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Transfer Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Performance Tuning

    4.4
    Rating, 4.4 out of 5 stars
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    1K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
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    U

    University of Minnesota

    Matrix Methods

    Skills you'll gain: Dimensionality Reduction, NumPy, Linear Algebra, Numerical Analysis, Statistical Methods, Regression Analysis, Mathematical Modeling, Applied Mathematics, Solution Design, Applied Machine Learning, Data Manipulation, Algorithms, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
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    248 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Introduction to RNN and DNN

    Skills you'll gain: Model Deployment, PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Artificial Intelligence, Applied Machine Learning, Artificial Neural Networks, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Machine Learning, Natural Language Processing, Supervised Learning, Network Architecture, Data Science

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
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    K

    Korea Advanced Institute of Science and Technology(KAIST)

    Math for AI beginner part 1 Linear Algebra

    Skills you'll gain: Linear Algebra, Artificial Intelligence, Applied Mathematics, Deep Learning, Machine Learning, Supervised Learning, Mathematical Modeling

    4.4
    Rating, 4.4 out of 5 stars
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    31 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Alberta

    Fundamentals of Reinforcement Learning

    Skills you'll gain: Reinforcement Learning, Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Markov Model, Algorithms, Probability Distribution

    4.8
    Rating, 4.8 out of 5 stars
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    2.9K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Data Science and Machine Learning with Python

    Skills you'll gain: Matplotlib, NumPy, Data Visualization, Data Manipulation, Linear Algebra, Seaborn, Natural Language Processing, Deep Learning, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Data Preprocessing, Data Science, Regression Analysis, Data Structures, Logistic Regression

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Convolutional Neural Networks

    Skills you'll gain: Convolutional Neural Networks, Computer Vision, Image Analysis, Transfer Learning, Deep Learning, Artificial Neural Networks, Keras (Neural Network Library), Tensorflow, PyTorch (Machine Learning Library), Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
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    43K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
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    N

    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

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    AI Fundamentals for Non-Data Scientists

    Skills you'll gain: Machine Learning Methods, Generative AI, Data Management, Big Data, Applied Machine Learning, Generative Adversarial Networks (GANs), Machine Learning, AI Product Strategy, Artificial Intelligence and Machine Learning (AI/ML), Autoencoders, Deep Learning, Model Evaluation, Algorithms, Data Analysis, Process Improvement and Optimization, Artificial Neural Networks

    4.8
    Rating, 4.8 out of 5 stars
    ·
    942 reviews

    Mixed · Course · 1 - 3 Months

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In summary, here are 10 of our most popular mathematical+foundations+of+neural+networks courses

  • Generative AI: Foundations and Concepts: Northeastern University
  • NVIDIA: Fundamentals of NLP and Transformers : Whizlabs
  • Deep Learning Frameworks and Neural Networks Simplified: Simplilearn
  • Deep Learning with Keras and Tensorflow: IBM
  • Matrix Methods: University of Minnesota
  • Introduction to RNN and DNN: Packt
  • Math for AI beginner part 1 Linear Algebra: Korea Advanced Institute of Science and Technology(KAIST)
  • Fundamentals of Reinforcement Learning: University of Alberta
  • Foundations of Data Science and Machine Learning with Python: Packt
  • Convolutional Neural Networks: DeepLearning.AI

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