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)"

  • Status: New

    Skills you'll gain: Model Evaluation, Fine-tuning, PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Model Training, Transfer Learning, Generative AI, Large Language Modeling, Natural Language Processing, Hugging Face, Generative Model Architectures, Data Preprocessing, Model Optimization, Data Processing, Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms

  • Status: New

    Skills you'll gain: Plotly, PyTorch (Machine Learning Library), NumPy, Matplotlib, Pandas (Python Package), Plot (Graphics), Data Visualization Software, Interactive Data Visualization, Machine Learning Methods, Python Programming, Applied Machine Learning, Scatter Plots, Numerical Analysis, Data Manipulation, Deep Learning, Image Analysis, Linear Algebra, Data Wrangling

  • Status: AI skills

    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: PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Model Evaluation, Convolutional Neural Networks, Natural Language Processing, Deep Learning, Generative Adversarial Networks (GANs), Classification Algorithms, Transfer Learning, Model Training, Vision Transformer (ViT), Artificial Intelligence and Machine Learning (AI/ML), Image Analysis, Fine-tuning, Artificial Neural Networks, Machine Learning, Computer Vision, Generative Model Architectures, Graph Theory, Machine Learning Algorithms

  • Status: AI skills

    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

  • Status: New

    Skills you'll gain: PyTorch (Machine Learning Library), Fine-tuning, Convolutional Neural Networks, Deep Learning, Natural Language Processing, Embeddings, Hugging Face, Computer Vision, Supervised Learning, Classification Algorithms, Data Preprocessing, Predictive Modeling, Machine Learning, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Statistical Methods, Probability & Statistics, Machine Learning Algorithms

  • Status: New

    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), Applied Machine Learning, Regression Analysis, Tensorflow, Supervised Learning, Deep Learning, Predictive Modeling, Machine Learning, Statistical Methods, Data Processing, Probability & Statistics

  • 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: Prompt Engineering, Large Language Modeling, Retrieval-Augmented Generation, Generative AI, PyTorch (Machine Learning Library), Prompt Patterns, Generative AI Agents, Fine-tuning, Vector Databases, LLM Application, Generative Model Architectures, Generative Adversarial Networks (GANs), Embeddings, Natural Language Processing, Tool Calling, Hugging Face, Model Optimization, Reinforcement Learning, Transfer Learning, Data Pipelines

  • Status: AI skills

    Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Statistical Modeling, Python Programming, Supervised Learning, Machine Learning, Agentic systems, Artificial Intelligence, Model Optimization, Algorithms, AI literacy

  • Status: New

    Skills you'll gain: Generative AI, Computer Vision, PyTorch (Machine Learning Library), Convolutional Neural Networks, Generative Adversarial Networks (GANs), Generative Model Architectures, Image Analysis, Fine-tuning, Artificial Neural Networks, Model Training, Applied Machine Learning, Model Evaluation, Deep Learning, Transfer Learning, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Optimization, Artificial Intelligence