Tag:Model

  • Google AI leader talks about machine learning trend in 2020: great breakthrough in multitasking and multimodality

    Time:2020-4-5

    Machine learning became a central topic at the neurips conference in Vancouver, Canada, last week. About 13000 researchers from all over the world focused on neuroscience, how to explain neural network output and how artificial intelligence can help solve major problems in the real world. During the meeting, Jeff Dean, the head of Google AI, […]

  • Baidu brain easyedge end model generation deployment strategy

    Time:2020-4-5

    Easyedge is an end computing model generation platform developed by Baidu based on paddy mobile, which can help deep learning developers quickly deploy their own models to the device end. Just upload the model, and the fastest 2 minutes can generate the end computing model and obtain the SDK. This paper introduces the calculation model […]

  • Nine of StarUML, some special properties of StarUML

    Time:2020-4-5

    UMLThe extensibility mechanism of allows you to expand in a controlled wayUMLLanguage. Such mechanisms include:stereotype, tag values, constraints. StereotypeExpandedUMLThe glossary allows you to create new building blocks that are inherited from existing ones, but specifically for your problems. Tag value expandedUMLThe building block properties allow you to create new information in the element‘s specifications. Constraints […]

  • Introduction to git branch management

    Time:2020-4-4

    Branch Management Version control and branch management of software run through the life cycle of the whole software product. Daily project management is also very important for the development team to deliver the software rhythmically and smoothly. This branch management and version control specification is mainly divided into three parts: branch management specification, version number […]

  • Tensorflow model continues to train fineturn instance

    Time:2020-4-3

    Solve the problem of how tenoflow continues to train fineturn on the trained model. Training code Task description: x = 3.0, y = 100.0, formula x × W + B = y, find the optimal solution of W and B. # -*- coding: utf-8 -*-) import tensorflow as tf #Declare occupation variables X, y x […]

  • Pipeline of spark mllib

    Time:2020-4-3

    The spark pipeline API is inspired by scikit learn and aims to simplify the creation, tuning and validation of machine learning processes.Ml pipeline usually consists of the following stages: Data preprocessing feature extraction Creation of algorithm model and fitting of model parameters Verification The phases of ML pipeline are implemented by a series of converters […]

  • Nltk natural language processing library

    Time:2020-4-2

    Natural language processing, usually referred to as NLP, is a branch of artificial intelligence, dealing with the interaction between computers and people using natural language. The ultimate goal of NLP is to read, interpret, understand and understand human language in a valuable way. Most NLP technologies rely on machine learning to extract meaning from human […]

  • Scikit flow series guidance of tensorflow practice: Part 1

    Time:2020-4-2

    Original address: here Google recently opened a machine learning framework tensorflow, which won more than 10k praise on GitHub in a short time, and caused a great response among AI researchers. Why do I care? Before we get to know tensorflow, we first need to understand a problem. As a professional data scientist, why do […]

  • Spark ml parameter

    Time:2020-4-1

    In machine learning, how to fit parameters for the algorithm model according to the given data set, so that the model can achieve the optimal effect, this process is called “tuning”.Spark’s mlib providesCrossValidatorandTrainValidationSplitThere are two ways to help tune the model.Generally, the following settings are required to use the above two methods, setEstimatorMethod to specify […]

  • Scikit flow series guidance of tensorflow: Part 2

    Time:2020-4-1

    Original address: here In this part, we will continue to go deep and try to build a multi-layer fully connected neural network, and customize the network model and try to convolute the network on this basis. Multi-layer fully connected neural network Of course, there are not many other linear / logistic fit frameworks. A basic […]

  • Summary of programming model (paradigm)

    Time:2020-3-31

    Preface In our daily life, we often encounter some nouns, such asCommand programming model,Declarative programming model,XXX language is object-orientedWait a minute, this programming model is everywhere, but what’s it all the time? What language and what programming model is it? When you are new to a language, some questions need to be considered first, such […]

  • Example of seq2seq model used by Python for NLP: neural machine translation with keras

    Time:2020-3-30

    Original link:http://tecdat.cn/?p=8438 In this paper, we will see how to create a language translation model, which is also a very famous application of neural machine translation. We will use the seq2seq architecture to create our language translation model through Python’s keras library. It is assumed that you have a good understanding of cyclic neural networks, […]