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    I need a clear explanation of Hopfield neural network with a solved example. No code is required The question should be answered: 1- What is the input? 2- Where is the input? 3-What and where is the output? 4- Why is learning formula? 5- how does it learn? 6- Why the formula has (2V-1)? Why not 3? 7- Clear formula with deep explanation for input/output/learning/training. Budget is $10.

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    detecting covid 19 samples using autoencoders

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    1. Collect and process pdf data dump from COVID-19 Open Research Dataset Challenge (CORD-19) [login to view URL] 2. Analyze the data and provide publication statistics such as the number of publications according to time, location but not limited to. Provide (any type of) visualization for the results. 3. Learn sentence embedding from the articles' abstract and main content respectively. ...

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    I have an image dataset that consist of different exposed(3 exposed images: low-medium-high) images and i have a registration network publicly available. I want this network to be trained and tested with this dataset. Registration task will be trained seperately on low-medium and high-medium exposed image pairs

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    We are working with a British economics think tank that has quite high impact (featured in the media etc). They would like to explore using machine learning to look at economics trends. This would primarily be using Python packages to keep things easy to begin with. We are a British outsourcing company and work with many companies here. We like to hire people on Freelancer and have a 100% 5 sta...

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    The research aims at finding out the following essential things. 1) Detecting multi-road lanes under complex weather conditions (fog, Snow, Dust, etc.) 2) Suppose road lane recognition can be enhanced with the road lane surface segmentation. 3) Increase lane detection reliability by using 3D detection methods/algorithms. Prefer to : 1) Adding non-intervention, for instance (with no lane marking)...

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    This is the second stage that dictates the selection of relevant feature vectors to train the predictive classifier. The relevant features are obtained from stock data and sentimental data. The objective of this stage is to find out the frequent trend patterns based on close price of a day with increased recall capacity, which is helpful for the time-series data. Here, a novel Hopfield Neural Ne...

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    Write a research paper 10 hours left
    VERIFIED

    I have the code for a Transformers Project, and a small report along with it showing the results. I need someone to convert the project into a research paper with less than 15% plagiarism.

    $7 / hr (Avg Bid)
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    Artificial Intelligence -- 3 9 hours left
    VERIFIED

    I will tell and find an AI python code, just need to know, just need you to do either one of these : - make one from scratch - fix/modify our old AI codes - convert our old AI codes from image to videos (or the other way around) Work Criteria: must be optimized and not slow must be at least 90% accurate the output as text values

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