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1. Basic steps for pytorch to realize linear regression Construct data setDefine Model function moduleConstruct the forward() function in the function module (that is, calculate y_pred)Calculate loss valueSelect optimization methodTraining cycle iteration 2. Several optimization methods of pytorch AdagradAdamAdamaxASGDLBFGSRMSpropRpr ...

[source code analysis] PyTorch distributed elastic training (6) - monitoring / fault tolerance 0x00 summary As for PyTorch elastic training, we have introduced Agent and rendezous respectively so far, but some parts are not in-depth, such as monitoring. This paper unifies them and logically combs the elastic training as a whole. The flex ...

Part of speech prediction by Python note42 LSTM Summary of all notes: Pytoch note Happy Planet Model introduction For a word, there will be different parts of speech. First, we can make a preliminary judgment according to the suffix of a word. For example, the suffix - ly is very likely to be an adverb. In addition, a same word can repre ...

This article continues with the last part. This article continues with examples of multi-catalog data training models. 4. Multi-directory data training This example is based on previous batch data training and repeated iteration training, and stores data files in multiple directories instead of just one directory to support distributed data a ...

1. Principal Component Analysis (PCA) Thought and Principle 1.1 What is principal component analysis PCA(Principal Component Analysis), a principal component analysis method, is the most widely used data dimension reduction algorithm (unsupervised machine learning method). Its main purpose is to "reduce dimensionality", by disjunct ...

In the first issue, we explained and realized the most basic linear regression. In this issue, we will talk about the regression problem to the classification problem. At this time, we need to add some elements based on the linear regression model, that is activation function so that our model can solve nonlinear data and classification pro ...

preface We will release Triton 1.0, an open source Python like programming language that enables researchers without CUDA experience to write efficient GPU code - in most cases equivalent to the code generated by experts. Triton makes it possible to reach the peak of hardware performance with relatively little effort; For example, it can b ...

Source: Hengyuan cloud community( Hengyuan cloud, a shared computing platform focusing on AI industry) Original address| Text data enhancement Original author Jiao Hui Recently, I was doing news headline classification and found an article with data enhancement to learn: One is enough! Overview of data enhancement methods This paper implem ...

Realize the step-by-step deepening from manual derivation to automatic derivation and then to the model. Implementation of two-layer neural network with numpy A fully connected ReLU neural network, a hidden layer, no bias, L2 Loss (h is hidden layer, ReLU activation function): h ...

In previous articles, we introduced some knowledge based on genetic algorithm. This article will use genetic algorithm to process machine learning model and time series data.Super parameter adjustment (TPOT)Automatic machine learning (Auto ML) helps us find the most suitable model for prediction by automating the whole machine learning process. ...