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    656 bert embeddings trabalhos encontrados, preços em USD

    My website has not really been optimised and it ranks poorly. I would like to improve the organic search hits and leads. I would like to know how it ranks now against competitors and after seo is complete. So I request a price for the initial SEO and if all well, ongoing support. Kind regards Bert

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    Python coding for NLP binary classification task. Knowledge in BERT-based models and Ensemble Learning is required.

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    Trophy icon I’m looking for a Logo Encerrado left

    Hi there, I need a logo that has “ The Bert and Shari Frizzell Family Foundation” in it. Something that looks professional

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    My project is nearly done, and it's a binary text classification by using the Google Bert Model. This project has the docker-compose to set up the environment, and the API is taking two text inputs and outputting the probability prediction score (0 to 1) which I expected, but it failed to output the score from the model. I need it to be fixed and output the score from the API POST request.

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    Zoumaville Encerrado left

    Bert and his brother Johan are 2 black bullfrogs and, with Bert's young tadpole they show us around the village where they live. We meet neighbour Basil Todd, out for a rise with his horse. When it refuses to jump over the hedge he grabs a branch and starts hitting the horse, using the same dialogue as when Basil Fawlty gives his car a "damn good thrashing". The bullfrogs head to the village rugby pitch to practise their kicking skills but realise they've forgotten to bring a ball with them. Undeterred they entice a nearby cat towards them. Bert persuades the tadpole to hold the cat down, like a player does for the kicker in windy conditions, before he kicks the cat between the posts for a conversion. "Kurzooma !!!" they shout in celebration. As ...

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    I am looking to have two men's faces blended with Bert and ernie as a work prank.

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    Project for Bert K. Encerrado left

    Hi Bert K., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

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    We have running project in PHP + Matlab. And now we have integrated BERT model using python and we are facing issue while integrating. So we require BERT model + python expert to fix this.

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    Hi Dharmam S., I noticed your profile and would like to offer you my project. I am working to implement BERT with ABSA

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    I have an existing notebook file that used to train binary classification, I want to reorganise the code with proper structure and builds a simple API with the FastAPI

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    Trophy icon Make 4 Different Monsters for a book Encerrado left

    ...MUST submit a monster for each character! When making your monsters make sure they are 3d looking vs 2d. Heres an example: 1) Loud and big Monster: Bert: Military, to the point: Doesn’t care what other people think, also very understanding and mutual on most topics. Plays a role of a monster that comes in with a loud crash and boom!! Berts Images are titled: “Bert 1, Bert 2, and Bert 3” 2) Sneaky skinny Monster: Cookie: Caring, Always there when you need her, but a trickster. Plays the role of a monster ready to get you but is hiding in the corner. Cookies Images are titled: “Cookie 1, Cookie 2, Cookie 3, Cookie 4 and Cookie 5” 3) small Funny Monster:

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    I am looking for very specific help troubleshooting a binary BERT classifier for text (built using a HuggingFace model). My classifier takes as input a training set and a test set and outputs probabilities of belonging to each class for each observation. My problem is simple: I do not know how to match the predicted probabilities with the observations to which they correspond. The output of the prediction has slightly fewer rows than the number of observations in the corresponding dataset, so I think some NA values must be getting dropped, but I don't know how to find out which ones they are. Ideally, the freelancer would take a look at the code and modify it so that when outputting probabilities, the code also outputs an additional column: the text that the probability was c...

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    Hello , I would like to replicate a relation extraction project that already has been published in the following article : I keep facing errors that possibly come from some incompatibility issues. I would like to outsource this project and expected that an expert can return a clean and reproducible notebook that I could rub in both google colab and AWS. As you can see in the attached file I have an issue with the final model generated by this project and also I am not able to use run_gpu neither in google colab nor in AWS sageMaker

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    trying to do a binary classification of whether or not a summary was created from a particular document. (Let the summary be Si, and each sentence of the summary Si be Sij, and the document be Dk, and each sentence of the document Dk be Dkl.) The summary Si is about 3 to 10 sentences, and a particular document Dk is more than 1000 sentences. <The characteristics of the dataset used are as follows.> There is a label to indicate whether or not a summary Si was created from a particular document Dk. There is no label to indicate which sentence of the summary Sij was created from which sentence of the specific document Dkl. There is no label to indicate which sentence of the summary Sij is made from which sentence of the specific document Dkl. Since there are many sentences of similar ...

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    Hello, I have a basic project that needs to change code in some python files (I had traced it, and I believed mainly in one python file). The task is to swap Word2Vec to BERT embedding. However, besides this assignment, I had more important stuff, so I am contacting you for your expertise. I have already traced the code and can provide you with the write-up of where I need to implement such changes. I have provided some files for you to check out. You can search for BERT inside the file to see which function may need to adjust. If you are available for this simple task, I'll send you the whole folder, for preview: I use to run the file main adjustments will be in

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    Hemos extraído los datos de Twitter haciendo uso de la herramienta Twint pero estamos teniendo dificultades con el análisis de estos mismo. Deseamos poder identificar la polaridad de los tweets (positivo, negativo, neutro), clasificarlos (a qué van referidos), el sentimiento pr...Twint pero estamos teniendo dificultades con el análisis de estos mismo. Deseamos poder identificar la polaridad de los tweets (positivo, negativo, neutro), clasificarlos (a qué van referidos), el sentimiento principal (tristeza, asco, miedo, enfado, alegría y sorpresa) y de ser posible la intensidad del tweet (leve, media, alta). Deseamos que este análisis se realice haciendo uso de las Word Embeddings en español y Redes Neuronales, pero si conocen de...

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    Bart transformer sentiment analysis .

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    I need help to write and execute code in python transformers to bert or other model on 2 or 3 data set and comper results

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    ...this repo there is a python file called . Wİth this file you can basically train a K-nn with dino features without any change. There is a variable called “distance” that is the main variable for entire k-nn (think like a loss function). We will use the same distance metric for creating a hierarchy. There is a paper called “Hierarchical Image Classification using Entailment Cone Embeddings” and they are using ETHEC dataset during their work. Paper Link : Dataset Link : In this paper they are used some different hierarchy methods for CNNs that are PLC, M-PLC and etc.(4 different approach) you can find the approaches

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    BERT ALBERTA ROBERTA LayoutLM and XML

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    We are looking for a program we can use to quickly analyze the top ESG topics mentioned in different companies' sustainability reports. We would like to be able to run 10-15 reports through the program and generate analyses of frequency of mention of material ESG terms (such as "diversity and belonging, diversity and inclusion") by company. We are thinking about using Google BERT-ESG or similar, but we are not programmers.

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    This project is a NLP project need to finish in 1 day Read the description in pdf

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    I'm looking for a data scientist with: - NLP experience, specifically around Python data stack (NumPy, Pandas) and related topic modeling and text classification work - experienced in relevant NLP/ML libraries (Gensim, LDA/NMF, BERT, GPT-x, etc.) - has knowledge and training around statistics / data science I'm trying to design a workflow that allows us to input a list of labels or topics to tag those articles. I need to be able to re-use the workflow across websites, each of which is very domain-specific. The deliverable should be a python notebook that allows me to: - configure number of topics in a topic modeling process based on the corpus - import a list of hand-identified labels we would like pages topics to be checked against - apply those labels appropriately to...

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    1. I am trying to create a text-based health information chatbot using google BERT neural network and knowledge graph. I have gotten some relevant codes from github for this. 2. The aim of my task is to enable the chatbot user to ask questions about certain different health questions or disease symptoms and get relevant replies from the chatbot. I have a health dataset in excel csv file (in Chinese). Also I need to show Recall, MRR or F1, and Precision accuracy scores 3. I need assistance from a freelancer with good knowledge of Python3 for coding NLP neural network and also CSS/HTML5/Swift because (a) the BERT and Knowledge Graph will be in Python3 and (b) the chatbot user GUI will be accessed online either on Web browser or IOS. 4. This work is my school assignment. I a...

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    Deep Learning Models Encerrado left

    over the given dataset, certain required deep learning models like BERT, CNN, transfer net, capsule net need to be implemented.

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    The UN has a list of categories for every product and service, called CPC. I would like to build a ML / BERT tool which will classify any product that I feed into it. For example:- Input: "Heinz 100% Tomato Soup". Output: "CPC Category: Canned Soup" Input: "Bottle of Merlot" Output: "CPC Category: Wine" Input: "Garden fresh purple sprouting" Output: "CPC Category: Broccoli.

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    Hi Justyna P., I need some help learning how to get BERT ML to work in Azure using Python. Is that an area of expertise for you? I'm new to BERT/Python/ML but I need to get my head around it to make a product classifier: I want to feed in a description of a product, and then get BERT/ML to say what category of thing it is.

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    Need help with topic modelling using LDA and BERTopic on a dataset

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    ...0>python --dataRoot "data/updated Control Scoring - " --out_file --modelDir checkpoints Traceback (most recent call last): File "", line 68, in <module> main() File "", line 61, in main scorer = Scorer(opts) File "C:UsersXC227CYDesktopcontrol scoring-main5.0utils", line 27, in __init__ self.PRC_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True) File "C:PythonPython37libsite-packagestransformers", line 1665, in from_pretrained use_auth_token=use_auth_token, File "C:PythonPython37libsite-packagestransformers", line 1142, in cached_path local_files_only=local_files_only, File "C:PythonPython37libsite-packagestransformers", line 1349, in

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    ...--dataRoot "data/updated Control Scoring - " --out_file --modelDir checkpoints Traceback (most recent call last): File "", line 68, in <module> main() File "", line 61, in main scorer = Scorer(opts) File "C:UsersXC227CYDesktopcontrol scoring-main5.0utils", line 27, in __init__ self.PRC_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True) File "C:PythonPython37libsite-packagestransformers", line 1665, in from_pretrained use_auth_token=use_auth_token, File "C:PythonPython37libsite-packagestransformers", line 1142, in cached_path local_files_only=local_files_only, File "C:PythonPython37libsite-packagestransformers&quo...

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    Research work -- 2 Encerrado left

    Research on Transformer architectures ,BERT , DL ,biLSTM

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    I need a NLP using Bert or spacy or gpt3 or any better one to do 1) NER and identify custom labels. 2) Based on labels identified a user should be able to train it by giving correct or false identification. 3) User should also be able to input some sentences to train the model like "abc is a software". Use case: Identify software names and component names from any pdf. Ping for more details

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    I need a NLP using Bert or spacy or gpt3 or any better one to do 1) NER and identify custom labels. 2) Based on labels identified a user should be able to train it by giving correct or false identification. 3) User should also be able to input some sentences to train the model like "abc is a software". Use case: Identify software names and component names from any pdf. Ping for more details Duration: A skeleton on or before Monday preferably. Less than a week would be good Note: Don't bid less and ask more. Project will be awarded after seeing some progress to eliminate stagers. This is just part of a poc if we get good accuracy then can be involved in further poc and main project.

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    Hi, I'm after a python script that I can use to: 1. Custom train a transformer such as Bert, AlBert, GPT etc on a custom data set. These datasets are customer service transcripts of either calls, emails or chat. This data will be supplied in CSV format as a series of documents where each row is a document. The basic header of the file would be: [ID, Text].The key here is I don't want to use any existing pre-trained models. I want to train each model for a specific use case with a large subset of sample text data. 2. With this trained model I then need to be able to generate document embeddings for a classified dataset. Basically, I need to be able to feed another CSV file into the model. This file would have a unique identifier for the document that enables it to m...

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    I want to learn data science with real time handson and projects. Technical skills like Python, Javascript, Pandas, Numpy, Scipy, Seaborn, Matplotlib, Plotly, Scikit learn & Tensorflow 2. x. Pytorch And Exposure to ANN, CNN, RNN / LSTM and BERT.

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    I have two Arabic social media datasets one is labeled (5 classes) and the other is not. The task is to use TensorFlow to train embeddings that classify the second dataset based on the 5 classes that exist in the first dataset. Then use a git repository to geotag the dataset. I need it to be in Google Colab notebook since I would want to learn and see step by step what happens. Would definitely need evaluation measures as well.

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    - PROJECT DETAILS 1# Develop artificial intelligence model based on already existing QUESTION ANSWERING (QA) as BERT on TENSORFLOW. 2# Train the model with data from UNI-T measurement and automotive diagnostic equipment LAUNCH. automotive LAUNCH diagnostic equipment. 3# Must be able to answer technical questions and give recommendations. which clamp works for refrigeration? Which scanner works for throttle body programming? Etc - SKILLS REQUIRED Machine Learning (ML); Data Science; Artificial Intelligence (AI) - BUDGET 45 USD - 50 USD - DEADLINE FRIDAY 17/09/21 - Send proposal of how the project will work FRIDAY 08/10/21 - Model test - Final touches THURSDAY 10/14/21 - Deliver the project FRIDAY 10/15/21 - Model vs. Members of the sales department - OPPORTUNITY Permanent work o...

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    ...test the implementation. The Natural Language Understanding module uses a TensorFlow models for character-based embeddings, intent-detection and slot-filling. The models contain following layers: - Bi-LSTM (Flair Embeddings) - Bi-GRU - CRF (from tensorflow_addons) In addition we currently perform tokenization using the word_tokenize method of the NLTK tokenizer package. This tokenizer can be replaced if required. For the implementation of this task we have following functional and non-functional requirements: Functional requirement 1.1: Implemented inference engine that is initialized from following arguments (example files can be found in the provided package): - the embeddings model - the intent/out-of-domain detection model - bio-tagging model - intent rul...

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    ... Familiarity and experience in neural-symbolic architectures / hybrid intelligence highly desirable - Familiarity and experience in program synthesis highly desirable - Experience in AutoML, with broad range of ML models (probabilistic, gradient boosting, DL, …) - Experience with Reinforcement Learning - Experience building/adapting/training language models, e.g. GPT [2, 3, Neo, J], BERT, etc. - Experience with time series / artificial intelligence techniques for transient behavior / time dependence, memory, and attention...

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    Hi All, This is a very interesting project. I believe you can find most of the code online (e.g see examples I found below) The goal is to understand r...4. Optional - generate new review base on the collected reviews and previous steps (***This is not must issue) Examples for similar projects that was done : Aggregate data by category and use BERT embeddings to find semantically related categories. Topic Modeling How to Use BERT to Generate Meta Descriptions at Scale

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    Summary: NLP project to read file and select specific table of document. Split the table row wise and create knowledge graph of it. Details: So the requirement is to build a project in python or jupyter notebook such that it reads text from pdf file(fitz library may suit the requirement). Select the specific table with keywords matching in...ipynb file with most of the reading file, extracting and cleanup. Deadline 3 days max as half of the work is done in the skeletal file I shall provide. 1 day would be awesome. This is just a poc level for now. If the quality is good we can have an extended project soon with accuracy check and additional features soon. Libraries n tools : Must:Jupyter, python, Recommend: fitz/pymupdf, spacy, nltk, Bert, networkx. Use any libraries that suit th...

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    Making resumes Encerrado left

    Hi! My name is Bert and i help ukrainians and usbekistan people to ho to work in europe (Most of them to Estonia) but before i can send details to employer. I have to make resumes of the workers where is information, where he live, age , name, photo of passport, photo of face, job he is specialist and so on.

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    research on EHR method for anonymising medical data using python. Natural language processing, machine leaning / deep learning, techniques, BERT etc.

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    ...practices( function description, example and 2 tests) Github/gitlab slack To reduce development cost and time, please try to build upon known models. All the functions should be build in a FLASK/Graphql API. Or do you have any better solution? ML Functions: Sentiment analysis of social media posts, articles, news, videos and shop reviews with sarcasm detection -> Bert /XLNET Translation Aspect extraction + sentiment for aspect -> Bert /XLNET Summarize text and video-> GPT-3 All above for videos, too Ai Articel writing out of gathered informations with seo friendly keywords -> GPT-3 Speech to text Detect fake/paid reviews -> AI video generation with synthetic avatar, voice, subtitle -> Objectextraction of image and create a 360° product image(see i...

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    NLP Python Encerrado left

    I'm working on disaster detection in Twitter. The task is to obtain a dataset, preprocessing, and clustering/classification in Python and using BERT.

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    Task is to build Attention based models on LSTM, GRU, Transformers. Previous experience on BERT, GPT, Transformers is required. Dataset will be provided. Need to implement the models in pytorch.

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    ... Familiarity and experience in neural-symbolic architectures / hybrid intelligence highly desirable - Familiarity and experience in program synthesis highly desirable - Experience in AutoML, with broad range of ML models (probabilistic, gradient boosting, DL, …) - Experience with Reinforcement Learning - Experience building/adapting/training language models, e.g. GPT [2, 3, Neo, J], BERT, etc. - Experience with time series / artificial intelligence techniques for transient behavior / time dependence, memory, and attention...

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    ...scores for that response. 2- I interested in analyzing text data with pre-trained models like BERT. 3- Representing the text as a bag-of-words n-gram model (probably unigrams, bigrams, and trigrams would be sufficient), and then compare the two approaches. 4- Report ------------------------------------------------- In other word: So I would like to develop an application for teachers that would allow them to automatically score and provide document summarization for students' open-ended written responses on assignments and tests. The procedure should be pretty straightforward: (1) Obtain the open-ended responses and accompanying rubric scores (2) Use bag-of-words or a pre-trained model like BERT to convert the text into features (3) Train a supervised algorit...

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    Task is to build Attention based models on LSTM, GRU, Transformers. Previous experience on BERT, GPT, Transformers is required. Dataset will be provided. Need to implement the models in pytorch.

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