Deep Learning

Practical AI Python Machine Learning and Deep Learning: PyTorch, CNN, Transfer Learning, GAN, RNN, LSTM, TCN, Object Detection

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Practical AI Python Machine Learning and Deep Learning: PyTorch, CNN, Transfer Learning, GAN, RNN, LSTM, TCN, Object Detection

01 Training Overview Python has become one of the most popular programming languages: according to the latest TIOBE rankings, Python has surpassed C# and is now among the top 4 most popular languages globally alongside Java, C, and C++. The simplicity, readability, and extensibility of Python, along with its numerous extension libraries, make it an … Read more

Understanding LSTMs: Long Short-Term Memory Networks

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Understanding LSTMs: Long Short-Term Memory Networks

In the previous article, we summarized RNNs (Recurrent Neural Networks). Due to the gradient vanishing problem in RNNs, it is challenging to handle long sequences of data. Experts have improved RNNs, resulting in a special case called LSTM (Long Short-Term Memory), which can avoid the gradient vanishing problem typical of conventional RNNs, thus gaining widespread … Read more

Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 2)

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Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 2)

For More Content, Please Follow: Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 1) Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 2) 23-24 Basics of Recurrent Neural Networks As shown above, sequence problems such as named entity recognition account for a significant proportion of real-life applications, while traditional machine learning … Read more

Multivariate Multi-Step Prediction Model Based on LSTM

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Multivariate Multi-Step Prediction Model Based on LSTM

♚ Author: Yishui Hancheng, CSDN Blog Expert, Research Directions: Machine Learning, Deep Learning, NLP, CV Blog: http://yishuihancheng.blog.csdn.net This article mainly practices multivariate sequence prediction based on LSTM (Long Short-Term Memory) neural networks, completing the prediction, analysis, and visualization of data at specified future time steps, and teaches you step by step how to build your … Read more

Deep Learning for NLP: ANNs, RNNs and LSTMs Explained!

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Deep Learning for NLP: ANNs, RNNs and LSTMs Explained!

Author: Jaime Zornoza, Technical University of Madrid Translation: Chen Zhiyan Proofreading: Wang Weili This article is approximately 3700 words, and it is recommended to read in 10+ minutes. This article will help you understand deep learning neural networks in a way never seen before, and build a Chatbot using NLP! Have you ever fantasized about … Read more

Can A Concise Architecture Be Efficient And Accurate? Tsinghua & Huawei Propose A New Residual Recurrent Super-Resolution Model: RRN!

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Can A Concise Architecture Be Efficient And Accurate? Tsinghua & Huawei Propose A New Residual Recurrent Super-Resolution Model: RRN!

Sharing a paper on video super-resolution titled Revisiting Temporal Modeling for Video Super-resolution, which is a BMVC 2020 paper. The results of this paper currently rank first on several datasets for video super-resolution, and the code has been open-sourced. Affiliations: Tsinghua University, New York University, Huawei Noah’s Ark Lab 1 Highlights This paper proposes a … Read more

Understanding LSTM: A Comprehensive Guide

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Understanding LSTM: A Comprehensive Guide

Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, I felt enlightened. This article … Read more

Overview of Deep Learning Models and Their Principles

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Overview of Deep Learning Models and Their Principles

Originally from Python AI Frontiers This article systematically and comprehensively organizes the introduction and algorithm principles of various deep learning models. 1 Main Text Deep learning methods utilize neural network models for advanced pattern recognition and automatic feature extraction, achieving significant results in the field of data mining in recent years. Common models include not … Read more

Understanding LSTM for Elementary Students

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Understanding LSTM for Elementary Students

Source: Machine Learning Algorithms Explained Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, … Read more

Understanding RNN (Recurrent Neural Networks) Basics

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Understanding RNN (Recurrent Neural Networks) Basics

Click the “MLNLP” above and select “Star” for the public account Heavy content delivered first-hand Author | Yi Zhen Address | https://zhuanlan.zhihu.com/p/30844905 Column | Machine Learning Algorithms and Natural Language Processing Understanding RNN (Recurrent Neural Networks) Basics Basics of Neural Networks Neural networks can be considered as black boxes that can fit any function. As … Read more