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  • Autoencoders

Results for "autoencoders"


  • I

    IBM

    Deep Learning with Keras and Tensorflow

    Skills you'll gain: Keras (Neural Network Library), Convolutional Neural Networks, Reinforcement Learning, Deep Learning, Model Optimization, Autoencoders, Generative AI, Unsupervised Learning, Tensorflow, Generative Adversarial Networks (GANs), Generative Model Architectures, Transfer Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Training, Time Series Analysis and Forecasting

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1K reviews

    Intermediate · Course · 1 - 3 Months

  • U

    University of Michigan

    Decoding AI: A Deep Dive into AI Models and Predictions

    Skills you'll gain: Generative AI, Model Evaluation, AI literacy, Data Ethics, Data Analysis, Model Training, Responsible AI, Data Literacy, Discussion Facilitation, Artificial Intelligence, Big Data, Predictive Modeling, Machine Learning, Social Impact

    4.8
    Rating, 4.8 out of 5 stars
    ·
    26 reviews

    Beginner · Course · 1 - 4 Weeks

  • P

    Packt

    Sequence Modeling, Transformers, and Transfer Learning

    Skills you'll gain: Recurrent Neural Networks (RNNs), Fine-tuning, Transfer Learning, Large Language Modeling, Natural Language Processing, Generative AI, Deep Learning, Artificial Neural Networks, Generative Model Architectures, Model Training, Computer Vision

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of Glasgow

    Generative Pre-trained Transformers (GPT)

    Skills you'll gain: Large Language Modeling, ChatGPT, LLM Application, Generative Model Architectures, Generative AI, Natural Language Processing, Embeddings, Responsible AI, Data Ethics, Model Evaluation

    4.4
    Rating, 4.4 out of 5 stars
    ·
    34 reviews

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of Pennsylvania

    AI Fundamentals for Non-Data Scientists

    Skills you'll gain: Machine Learning Methods, Generative AI, Data Management, Generative Model Architectures, Big Data, Statistical Machine Learning, Applied Machine Learning, Machine Learning Algorithms, Generative Adversarial Networks (GANs), Machine Learning, AI Product Strategy, Large Language Modeling, Customer Data Management, AI literacy, Autoencoders, Model Optimization, Deep Learning, Model Evaluation, Algorithms, Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1K reviews

    Mixed · Course · 1 - 3 Months

  • D

    DeepLearning.AI

    Natural Language Processing with Attention Models

    Skills you'll gain: Natural Language Processing, Transfer Learning, Fine-tuning, Recurrent Neural Networks (RNNs), Applied Machine Learning, Keras (Neural Network Library), Model Evaluation

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1.1K reviews

    Intermediate · Course · 1 - 4 Weeks

  • S

    Simplilearn

    Foundations of Generative AI Models

    Skills you'll gain: Generative Model Architectures, Retrieval-Augmented Generation, Generative AI, Generative Adversarial Networks (GANs), Autoencoders, Model Training, Model Evaluation, Large Language Modeling, Real Time Data, Scalability, Responsible AI

    Beginner · Course · 1 - 4 Weeks

  • P

    Packt

    Advanced Generative Adversarial Networks (GANs)

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Generative Model Architectures, Model Optimization, Transfer Learning, Artificial Neural Networks, Keras (Neural Network Library), Image Analysis, Convolutional Neural Networks, Deep Learning, Tensorflow, Data Preprocessing, Embeddings, Model Training, Network Architecture

    Advanced · Course · 3 - 6 Months

  • N

    National Taiwan University

    人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)

    Skills you'll gain: Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Theoretical Computer Science, Classification Algorithms, Machine Learning Methods, Artificial Neural Networks, Artificial Intelligence, Machine Learning Algorithms, Applied Machine Learning, Machine Learning, Model Evaluation, Autoencoders, Convolutional Neural Networks, Supervised Learning, Statistical Machine Learning, Computer Science, Decision Tree Learning, Generative Adversarial Networks (GANs), Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    62 reviews

    Intermediate · Course · 1 - 3 Months

  • N

    Northeastern University

    Statistical Learning for Engineering Part 2

    Skills you'll gain: PyTorch (Machine Learning Library), Applied Machine Learning, Unsupervised Learning, Reinforcement Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning Methods, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Decision Tree Learning, Autoencoders, Model Optimization

    Intermediate · Course · 1 - 3 Months

  • P

    Pearson

    Programming Generative AI: Unit 2

    Skills you'll gain: Generative AI, Large Language Modeling, Generative Model Architectures, Image Analysis, Autoencoders, Hugging Face, Embeddings, Computer Vision, Convolutional Neural Networks, PyTorch (Machine Learning Library), LLM Application, Natural Language Processing, Image Quality, Model Training

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Deep Learning: Convolutional Neural Networks with TensorFlow

    Skills you'll gain: Transfer Learning, Keras (Neural Network Library), Fine-tuning, Embeddings, Deep Learning, Image Analysis, Artificial Neural Networks, Computer Vision, Natural Language Processing, Data Preprocessing, Model Optimization, Model Training

    Intermediate · Course · 1 - 4 Weeks

1…567…12

In summary, here are 10 of our most popular autoencoders courses

  • Deep Learning with Keras and Tensorflow: IBM
  • Decoding AI: A Deep Dive into AI Models and Predictions: University of Michigan
  • Sequence Modeling, Transformers, and Transfer Learning: Packt
  • Generative Pre-trained Transformers (GPT): University of Glasgow
  • AI Fundamentals for Non-Data Scientists: University of Pennsylvania
  • Natural Language Processing with Attention Models: DeepLearning.AI
  • Foundations of Generative AI Models: Simplilearn
  • Advanced Generative Adversarial Networks (GANs): Packt
  • 人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory): National Taiwan University
  • Statistical Learning for Engineering Part 2: Northeastern University

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