Tag：pytorch
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SENet code replication + annotation (PyTorch)
The SENet module is often used for channel attention in convolutional networks to enhance the network model’s ability to select in channel weights and thus lift points. About the principle and specific details of SENet, we have already described in detail in the previous article:Ultra-detailed Explanation of Classical Neural Network Papers (VII) – SENet (Attention […]
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Simple use of Segment Anything (SAM) demos
If you think the article is okay, can you give it a like? Your likes are what keep me updated! catalogs SAM demo source code usage A case study of HCI ui usage in conjunction with SAM: Recently newly discovered, you can use this model, a simple UI use, the effect is as follows: Labelimg […]
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Building Neural Networks with PyTorch
PyTorch Deep Learning in Action (3) – Building Neural Networks with PyTorch 0. Preface1. PyTorch building neural network first experience1.1 Building Neural Networks with PyTorch1.2 Neural network data loading1.3 Model testing1.4 Getting the value of the middle layer 2. Using Sequential Classes to Build Neural Networks3. Saving and loading PyTorch models3.1 Components required for model […]
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Neural Networks and Model Training Process in Detail
PyTorch Deep Learning in Action (1) – Neural Network and Model Training Process in Detail 0. Preface1. Traditional machine learning and artificial intelligence2. Basics of artificial neural networks2.1 Artificial Neural Network Composition2.2 Training of Neural Networks 3. Forward dissemination3.1 Calculating hidden layer values3.2 Perform nonlinear activation3.3 Calculating the output layer values3.4 Calculation of the value […]
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Transformer Code Explained (Pytorch Edition)
preamble Based on the previous postClassical Network Architecture Learning-TransformerThe study, today we use pytorch to build their own transformer model, to deepen the understanding of transformer, not only in the field of NLP can not get around the transformer, but also in the field of CV is also very hot, a lot of models are […]
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Python’s method for importing torch packages
Article Catalog preambleI. What is Pythorch?Second, how to download and import the torch package?Third, pip package manager download failure torch, the solution and the official website to download teaching1. Download failure, solution2.Official website download Fourth, why there will be the official website to download and local direct download, torch two ways?summarize preamble With the continuous […]
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OpenAI’s Artificial Intelligence Speech Recognition Model Whisper Explained and Used
1 whisper Introduction OpenAI, the company that owns the ChatGPT language model, has open-sourced the Whisper automated speech recognition system, and OpenAI emphasizes that Whisper’s speech recognition ability has reached the human level. Whisper is a general-purpose speech recognition model trained using a large amount of multilingual and multi-task supervised data, capable of achieving near-human […]
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Quantum computing frameworks and libraries TensorFlow Quantum, PyTorch Quantum can be used for deep learning
catalogs 1. Install TensorFlow Quantum:2. Install PyTorch Quantum:3. Case study: quantum linear regression How to install TensorFlow Quantum and PyTorch Quantum with some simple code examples. Please note that since quantum computing is still in the early stages of development, these tools and libraries may change over time 1. Install TensorFlow Quantum: First, you need […]
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Wise Target Detection 66 – Pytorch builds YoloV8 target detection platform
Wise Target Detection 66 – Pytorch builds YoloV8 target detection platform Preface to the studySource Code DownloadYoloV8 Improvements (incomplete)YoloV8 Implementation IdeasI. Overall structural analysisII. Network structure analysis1. Introduction to Backbone, the backbone network2. construct FPN feature pyramid for enhanced feature extraction3. Use Yolo Head to obtain predicted results III. Decoding of forecast results1. Getting the […]
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NLP machine translation panorama: from the basic principles to the full analysis of technical practice
catalogs I. Introduction to Machine Translation1. What is Machine Translation (MT)?2. Source and target languages3. Translation models4. Importance of context II. Rule-Based Machine Translation (RBMT)1. Rule-making2. Dictionaries and vocabulary selection3. Constraints and challenges4. PyTorch implementation III. Statistical Machine Translation (SMT)1. Data-driven2. Phrase alignment3. Scoring and selection4. PyTorch implementation IV. Neural network-based machine translation1. Encoder-Decoder structure2. […]