PyTorch (Machine Learning Library)

PyTorch is an open-source machine learning library, designed for maximum flexibility and speed in the implementation of deep neural networks. Coursera's PyTorch catalogue teaches you about this powerful tool created by Facebook's artificial intelligence research group. You'll learn everything from the basics of PyTorch, tensor operations, auto gradients, to the designing and training of neural networks for machine learning and artificial intelligence. You'll also explore practical applications of PyTorch in image and language processing, reinforcement learning, and more. This skill is essential for AI researchers, data scientists and anyone interested in the field of machine learning.

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Results for "PyTorch (Machine Learning Library)"

  • Skills you'll gain: PyTorch (Machine Learning Library), Model Deployment, Hugging Face, Model Optimization, Fine-tuning, Convolutional Neural Networks, Transfer Learning, Data Quality, Generative AI, Data Manipulation, Deep Learning, Generative Model Architectures, Model Training, Image Analysis, MLOps (Machine Learning Operations), Large Language Modeling, Data Pipelines, Artificial Neural Networks, Computer Vision, Natural Language Processing

  • Skills you'll gain: Model Deployment, Fine-tuning, PyTorch (Machine Learning Library), Model Evaluation, Model Training, Vision Transformer (ViT), Model Optimization, Transfer Learning, MLOps (Machine Learning Operations), Natural Language Processing, Debugging, Containerization, Kubernetes, Docker (Software), Distributed Computing, Performance Tuning, Tensorflow, Deep Learning, Cloud Computing, Data Pipelines

  • Skills you'll gain: PyTorch (Machine Learning Library), Model Optimization, Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Transfer Learning, Autoencoders, Generative AI, Unsupervised Learning, Tensorflow, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Generative Model Architectures, Model Training, Logistic Regression, Image Analysis, Applied Machine Learning, Regression Analysis

  • Skills you'll gain: Model Deployment, Unit Testing, MLOps (Machine Learning Operations), Kubernetes, Docker (Software), Containerization, Test Driven Development (TDD), Application Deployment, Continuous Integration, Software Testing, Model Training, CI/CD, Scalability, Scikit Learn (Machine Learning Library), Tensorflow, PyTorch (Machine Learning Library), Performance Tuning, Python Programming, Software Engineering, Git (Version Control System)

  • Skills you'll gain: Generative Adversarial Networks (GANs), Artificial Intelligence and Machine Learning (AI/ML), Exploratory Data Analysis, Model Deployment, Generative AI, Keras (Neural Network Library), NumPy, Model Optimization, Applied Machine Learning, Data Processing, PyTorch (Machine Learning Library), Predictive Modeling, Matplotlib, Data Analysis, Generative Model Architectures, Deep Learning, Transfer Learning, Artificial Intelligence, Machine Learning, Data Science

  • Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Retrieval-Augmented Generation, PyTorch (Machine Learning Library), Computer Vision, Unsupervised Learning, Generative Model Architectures, Prompt Patterns, Generative AI, PySpark, Model Optimization, Keras (Neural Network Library), Supervised Learning, LLM Application, Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science

  • Skills you'll gain: Natural Language Processing, Large Language Modeling, Fine-tuning, Model Evaluation, Recurrent Neural Networks (RNNs), Data Ethics, Responsible AI, Text Mining, Transfer Learning, PyTorch (Machine Learning Library), Artificial Neural Networks, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Applied Machine Learning, Data Processing, Machine Learning, Data Analysis, Data Cleansing

  • Skills you'll gain: Unsupervised Learning, Seaborn, Matplotlib, Predictive Modeling, Data Preprocessing, Supervised Learning, NumPy, Plot (Graphics), Model Evaluation, Applied Machine Learning, Predictive Analytics, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, PyTorch (Machine Learning Library), Scatter Plots, Python Programming, Data Science, Machine Learning, Data Analysis

  • Skills you'll gain: PyTorch (Machine Learning Library), Model Optimization, Transfer Learning, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Model Training, Logistic Regression, Image Analysis, Applied Machine Learning, Model Evaluation, Computer Vision, Classification Algorithms, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Statistical Methods

  • Skills you'll gain: Generative AI, Fine-tuning, Large Language Modeling, Generative Model Architectures, Model Optimization, Prompt Engineering, Model Training, PyTorch (Machine Learning Library)

  • Skills you'll gain: PyTorch (Machine Learning Library), Computer Vision, NumPy, Matplotlib, Convolutional Neural Networks, Deep Learning, Pandas (Python Package), Image Analysis, Model Optimization, Python Programming, Data Manipulation, Model Training

  • Johns Hopkins University

    Skills you'll gain: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Machine Learning Methods, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Model Training, Machine Learning, Deep Learning, Model Optimization