Introduction Have you ever felt overwhelmed by the complexity of deep learning? Have you heard of the powerful tool known as Convolutional Neural Networks (CNN) but found it confusing? Don’t worry! This article will guide you step by step through the core concepts of CNN and teach you how to easily build and train a … Read more
Cover Image: Airbnb Headquarters, Illustrated in March 2020 Recently, while exploring artificial intelligence, I felt that among the materials available, there is a lot of information that can yield results through programming steps, but many people regard this process as a black box. It is often said that we do not know why this process … Read more
RNN is a popular model for processing time series data, demonstrating significant effectiveness in fields such as NLP and time series forecasting.As this article focuses on the practical application of RNN rather than theoretical knowledge, interested readers are encouraged to study RNN systematically. The following example is implemented using TensorFlow.Using TensorFlow to implement RNN or … Read more
Selected by OpenAI Author: JAKOB FOERSTER Translation by Machine Heart Using linear networks for nonlinear computation is an unconventional approach. Recently, OpenAI published a blog introducing their new research on deep linear networks, which do not use activation functions, yet achieve 99% training accuracy and 96.7% testing accuracy on MNIST. This new research has reignited … Read more
In the previous article, we learned about the basic seq2seq model, which processes the input sequence through an encoder, passes the calculated hidden state to a decoder, and then decodes it to obtain the output sequence. The block diagram is shown again below: The basic seq2seq model is quite effective for short and medium-length sentences … Read more
Author: Pulkit Sharma; Translator: Wang Weili; Proofreader: Ding Nanya This article is about 3400 words, recommended reading time is 10 minutes. This article introduces the process of building a deep learning model for image recognition, providing a basic framework for beginners to solve image recognition problems by stating the actual competition problem, introducing the model … Read more
Translation | Yu Zhipeng Lin Xiao Proofreading | Cheng Sijie Compiled | Kong Lingshuang | AI Study Group Introduction The Word2Vec model is used to learn vector representations of words, which we call “word embeddings”. Typically, it serves as a preprocessing step, after which the word vectors are fed into a discriminative model (usually RNN) … Read more
DeepNude algorithm “removing” clothes – Welfare Bar http://fulibus.net/deepnude.html First, the file is as shown Deep learning computer vision (speculated) Image Inpainting You can refer to NVIDIA’s paper using partial convolution and partial convolution-based filling to repair images with irregular holes. The code part of the paper is converted. Paper address: https://arxiv.org/abs/1804.07723 and https://arxiv.org/abs/1811.11718 In the … Read more
Course Swift for TensorFlow Swift for TensorFlow combines the flexibility of Eager Execution with the high performance of graphs and sessions. Swift can analyze your Tensor code in the background and automatically build graphs. It also captures type errors and shape mismatches before running the code, allows input from any Python library, and features language-integrated … Read more
There are many ways to install TensorFlow. This article will provide a detailed guide on how to install TensorFlow using pip. Available Installation Packages tensorflow — Current version for CPU only (recommended for beginners) tensorflow-gpu — Current version with GPU support (Ubuntu and Windows) tf-nightly — Nightly build for CPU only (unstable) tf-nightly-gpu — Nightly … Read more