Python is a high-level general purpose programming language, and its open source machine learning library is called Pytorch. It is currently being utilized by two of the tech sector’s most valuable companies, Facebook and Uber, who utilize it for different reasons. It is considered one of the most important tools in artificial intelligence today. It provides two main features, which include tensor computation, in addition to deep neural networks. The language is also known for utilizing a technique called automatic differentiation, which allows for rapid machine learning.

One of the most important aspects for automation and the internet of things is the idea of natural language processing, which allows human beings to interact with devices through voice. Human beings understand that the more that computers understand human languages, the more that automation can occur, not to mention real-world applications, such as language translation and transcription.

Pytorch is one of the most important libraries related to machine learning and deep learning, that is already being used by multiple Fortune 500 companies. Its relevancy will only increase the more that we move towards using artificial intelligence in everyday technology, and Pytorch can be a tool that can optimize countless companies exponentially.

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    The project is taking handwritten word images as input and pass through a CNN followed by RNN. In the end, a CTC decoder is used to decode the text back into printed format. The detailed architecture is shown in the block diagram attached. The model is implemented, now the next task is to replace RNN with CNN for the sequence to sequence mapping of word characters.

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    I have two ready GitHub repos with official implementations of deep learning papers in the field of video classification. I need help running those repos on a different dataset that I have. I need to do training and inference using both repos on my target dataset. Therefore, we have a total of 4 requirements: training on repo 1, inference on repo 1, training on repo 2, inference on repo 2. The re...

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    1. Build a base model (LSTM) 2. Implement Various attention models on top of base model [se connecter pour voir l'URL] and compare the accuracy of the model with at least two Datasets **Requirements may change according to the time**

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    Please note that **Requirements may change according to the time** 1. Build a base model (LSTM) 2. Implement Various attention models on top of base model [se connecter pour voir l'URL] and compare the accuracy of the model with at least two Datasets

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    They are two tasks one is one Classification. No time wasters please

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    Pytorch model modification 2 jours left
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    Very small work needed. I need to save the model in a darknet weight file from 2 repo. Need to finish soon. No running the model. No dataset required. It's just python work. Cannot pay more than the budget. Let's talk

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    a project is written in TensorFlow v 1 and I need to translate it into the current PyTorch version. It relates to graph convolution network and Bayesian inference and Stochastic block model. I need an engineering expert on the topics and need it delivered within 5 days, in total 10 files.

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    Looking for someone to write a well structured project report (10 pages single spaced), of a running Pytorch code on image classification. coding has been done, and only needs a final report to be done. If you are good in such skills, and you can test the code to understand it, and then do the report, kindly contact

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    Experience in OCR with pytorch 11 heures left
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    Need to train a license plate recognition end to end. Please bid only if you experience.

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    I need an expert in computer vision who have experience with crowding projects

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