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    5,514 online dating dataset jobs fundet, i prisklassen EUR

    ... Ikke alle kurser kan have alle de studenter der søger, hvorfor dem med størst præference skal fordeles hertil. Der skal ligeledes udarbejdes en userform, da der er flere dataset at vælge imellem. ...

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    5 bud

    ...Objectives Predicting the outcome of English premier league which is most popular and followed by people all over the world. Get the accuracy rate of over 70%. Pre-processing dataset to refine the data. Compare different machine learning algorithms and find out the best accuracy. Implement it on various data sets to see the outcome. Investigate the pre-processing

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    ...training. We also introduce a new large-scale first of its kind dataset of 128 hours of videos. It consists of 1900 long and untrimmed real-world surveillance videos, with 13 realistic anomalies such as fighting, road accident, burglary, robbery, etc. as well as normal activities. This dataset can be usedfortwotasks. First,generalanomalydetectionconside

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    ...recurrence of the disease among the patients based on important stated parameters. The paper highlights the performance of different shows that classification algorithms on the dataset. Applying different data mining techniques and find the better solution for Breast Cancer....

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    Prototype is complete. CSS/HTML front end and React / JS back end pulling from a dataset - need prototype developed and admin panel added.

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    Create 5 clases in python that implement the following methods: 1. Principal Component Analysis; 2. Factor Analysis or Explorator...about the project requirements in the following document. I am interested in having the bullet points from a) to h), meaning 5-6 points I can provide you with documentation,dataset and examples of classes already started

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    I have a dataset which I want to transform into reports and charts. Like employee performance and similar.

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    Object detection deep learning 1 5 dage left
    VERIFICERET

    ...source code but i need to run it object detection deeplearning project using three different models : 1/YOLO 2/SSD 3/RetinaNet training of the models should be for the same Dataset. and the output needed is two graphs one of them compare the accuracy of the models , the other is to compare the speed of the models. the project should be made using Python

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    I want to prepare examination dataset consisting of questions and answers. The focus is on technical skills. It should be in objective question format (1Q-4A) and subjective for code related task. Language: en-UK The questions should be original. If they are taken from somewhere then you need to check copyright and license terms, disclose it

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    I want a simple Network that use the Convolutional Neural Network able to do create an High Resolution Image from a Low ...builded. - Prediction comparison must be done: between the generated SR image w.r.t to the LR. between the generated SR image w.r.t to the given HR. - Freely to use a dataset that containts LR image and the same image in HR

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    I want to prepare test dataset consisting of questions and answers. The focus is on technical skills. It should be in objective question format (1Q-4A) and subjective for code related task. Language: en-UK The questions should be original. If they are taken from somewhere then you need to check copyright and license terms, disclose it to me.

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    Budget = 50$ The development of an Assistant helps the automation of cancer diagnosis. If a large dataset is available, it is possible to have recommendation methodologies that automatically can classify the set of medical images and lesions detection, giving a high probability to those cases where intervention is necessary. These methodologies will

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    Human action recognition on unity 4 dage left
    VERIFICERET

    I want a very simple program for unity if I clap my hands in from of webcam program...use any action instead of clapping (jumping, typing etc..) the program should train itself from a dataset (here is the example link of dataset : [log ind for at se URL]) (programmer can use any dataset . I can also give a dataset) thanks

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    I need a query to extract the previous 10 values of a custom session level dimension before a purchase event and the value at time of purchase. This is from a Google 360 dataset running advanced eCommerce. Purpose is to track the accuracy of custom Audience modelling. From the results I need to: Validate product purchased matches Audience value

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    Haster
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    ...The script need to take the text messages and filter it based on the the dictionary table ([log ind for at se URL]) If you are using tokenizer to find "word", please note that in this dataset: 1) punctuation itself is also considered a word 2) it is not case sensitive, e.g. china = China Therefore for a text "how I loathe thy tasty good" if only the word "thy...

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    I would like to have an HTML component de...temporary window with the timestamp in it Moving the mouse cursor away from the selected point will cause the temporary window to disapear I've attached a sample json dataset to help visualize what kind of data will be used within this component The component should be delivered in HTML/css/javascript

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    7 indlæg

    Dataset: UC Merced Land Use Dataset [log ind for at se URL] Apply feature extractions algorithms: . Color Histogram [log ind for at se URL] And choose a statistical analysis/modeling (Histogram/ PDF and statistical test, Statistical moments, Covariance analysis or

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    Project requirement is very simple. The only skill needed is to read and speak Burmese fluently (native speaker). We will provide a 24000+ Burmese sentences, you just have to read the sentence aloud and record it. We will provide a dedicated Android app to make the process faster. A few requirements - #1 - Total audio duration: 42 hours #2 - Total number of different speakers: 10-15 person (each...

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    Build a Recommender System using NLP And RNN (Deep Learning) for the following dataset based on the overall reviews, review votes etc usefull columns. dataset link : [log ind for at se URL]

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    ...detection is needed. - I prefer to have it coded in Python, but if you believe something else suits this task better, I'm open to hear more. - I'd like to see the model and dataset become better as time goes along, and it gets more images (data) uploaded from the users, so if the user gives his/her permission to store the image, the model would be required

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    I want a simple NN that Is able to transform a Low Resolution image to high resolution image. The dataset has both type of image, LR, and HR. I'm not interested in very high performance... Instead I need 3 type of NN. 1 By using SCNN approach. 2. By using Variational Autoencoders 3. By using Gan. I will repeat that I'm not interested in very

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    ...There are two different ways to interpret the data so we'd like these to be separated by tabs on the front end. For example, averages per person or averages per location. The dataset will be very small and will not grow very quickly. Maybe +500 records a week. We are not concerned with fault tolerance or high availability. Challenges: We can point you

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    I want to build model help to classify 7 types of skin diseases using deep learning. Also the dataset highly unbalanced so we need to doing preprocessing such as ( Data augmentation , SMOTE method or geometric transformation ). Also I want to investigate if the segmentation of the image will enhanced the measure of classification. Already i try to do

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    I have a dataset that I need to analyse in SAS and then interpret it. I will provide the details in the chat.

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    I have use inception model to classsify my images dataset. I just need to save the Accuracy BAtch file permanently so it will use the save training file instead of train the model everytime i will run the project. Second thing is to set a path for test image so that i can test the model. these are very little task so i need someone who can transfer

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    perform RNN (recurrent neural network) on dataset in python using LSTM pr GRU

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    I'm getting "nan" as loss value while training my LSTM model...getting "nan" as loss value while training my LSTM model. Im have a dataset of 3648 rows. Number of LSTM layer : 4 Number of neurons in one LSTM : 50 Dropout : 0.2 Optimizer : Adam Loss : mean_squared_error Epochs : 100 batch size : 32. Please find attached the source code and the dataset.

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    Project for Joao S. Udløbet left

    Hi Joao S., you did some medical stats for my wife recently. She has now a new dataset. Could you do that? For somebody of your calibre it should be a matter of just a few minutes. Best regards Peter

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    Project requirement is very simple. The only skill needed is to read and speak Burmese fluently (native speaker). We will provide a 24000+ Burmese sentences, you just have to read the sentence aloud and record it. We will provide a dedicated Android app to make the process faster. A few requirements - #1 - Total audio duration: 39 hours #2 - Total number of different speakers: 10-15 person (eac...

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    23 bud

    I need to write and implement the baseline algorithm in the attached paper "Efficient and Load Balancing Strategy ...implement the baseline algorithm in the attached paper "Efficient and Load Balancing Strategy for Task Scheduling in Spatial Crowdsourcing" using java. then run it using dataset SCAWQ please add the comments for each step in the code.

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    Hello, I have a decent number of formulas I need applied to a large dataset of forex quotes that I have. The file with the dataset is attached. I need the 14 period RSI calculated, the 20 period CCI calculated, the 16 period ADX, the high minus the low, and the 8 and 34 period EMAs. Please tell me how much this would cost. Preferably also, I would be

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    ...contains many departments, and you must project the sales for each department in each store. To add to the challenge, selected holiday markdown events are included in the dataset. These markdowns are known to affect sales, but it is challenging to predict which departments are affected and the extent of the impact. You will be evaluated on the weighted

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    Need to Build A symptom checker which can predict a disease / help in diagnosing a disease when symptoms r entered . Curate a disease symptom dataset and perform machine learning / data mining and create a model that can perform this particular task.

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    I have a large dataset with daily weather and pollution variables (~20 variables) over a 3 year period as well as data on daily hospital emergency department attendance over this same period. I would like to see how well one can predict patient attendance using this weather and pollution data. Multiple linear regression has not worked well enough to

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    Verilen dataset ile tensorflow modelinin eğitilmesi ve tensorflow kullanarak oluşan .pb dosyasının .tflite dosyasına dönüştürülmesi.

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    Goal: we want to have a dataset of the best 750 restaurants in Amsterdam. This must be written in Python 3+ and the output should be a dataframe (or similar). 1. Go to: [log ind for at se URL] a. If you scroll down you will see the rankings. In total there are 3604 restaurants in this

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    A recommender system using python and lenskit for a small dataset (from movielens) for practice and understanding, should be an easy task, not more than 100 lines of code.

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    I want to collect dataset(sentence) from imdb movie synopsis section and then classify each sentence according to the 8 emotion classes(Joy,Sad,Anger,Surprise,Fear,Disgust,Love,Neutral). This has to be done manually. [I'm doing emotion classifier for movie synopsis for that I want dataset from imdb synospis (senetence) and then save it to a excel file

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    ...application. Word cloud associates with the topic of road traffic accidents / car accidents when a user starts to type into a search box. Scatter graphs comparing months of each dataset to look for patterns, use clustering algorithms and other algorithms; like k means. Take facts and statistics on road traffic accidents I give you, use mysql as database.

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    R multithreading expertise required to conduct basic analysis on a large dataset.

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    To Train Face detection model based on Deep learning CNN. The purpose ...purpose of this face detection model is to detect accurately faces in Occlusion . To do that . A model has to be trained on large datasets which contains occluded faces. The dataset is partially prepared and not yet available . there is still need to do ground truth labeling.

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    Hello, You can see in the uploaded "[log ind for at se URL]" how the DataSet should look like. The data should represent orders of a online fashion shop. One order can contain several articles. The generated DataSet can be simplified: OrderID can start with 1; ArticleID could be 1-50; deviceID is not needed; voucherAmount could just be 5, 15 or 30

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    email spam/ham Udløbet left

    ...Random Forest 4. Others which can work well on this dataset. For the above mentioned goal, we will be following below mentioned steps to fulfill each of the goals: 1. Exploring the Enron Dataset This involves data cleaning, outlier removal and analyzing. 2. Feature processing of the Enron dataset It includes feature creation, feature scaling, feature

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    I am working on Tensorflow Api, and I have already trained my dataset. It works fine. But I have to crop the detected object and make some preprocess on it. It seems easy, because Tensroflow draws the detected object with green box as well. When I try to find the coordinates of the object it gives me numbers of range 0 to 1. When I put the coordinates

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    I have an Excel file with 19 columns, In each column, we have between 5 to 45 values. Each column has a header. Output: I would like a new Excel file where we would have the same number of columns, the same column headers and, on each line, we would have a different combination of values (these values will be picked from the values we have in the same columns in the initial Excel file). We'...

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    [log ind for at se URL] would like this converted to run on irrlicht in c++ using online dataset.

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    This project is to analyze data and generates a rule to classify that data. For example, give...the rule and threshold values for each feature or variable. In this case threshold values are 30 for X1, 15 for X2 and 10 for X3. I was able to generate the rule for small dataset but the accuracy was only 60%, in addition, I couldn't find threshold values.

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    SAS-Analysis Udløbet left

    ... The project consists on the formulation of a marketing problem and the corresponding research using a set of relevant quantitative methods. -Its a quite simple and easy dataset, where you find just 10 items, all measured on a 5-point rating scale Expectation: Clearly explain the problem and define the research objective; • Discuss the available methodologies

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    Dataset Annotation Udløbet left

    I want to hire a freelancer to annotate the given dataset within 1.5 week. Dataset size is around 6k images

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    I have attached an dataset that I have solved with neural network and I am getting a reasonable solution. I would like to set up two additional solutions for the same data set with Gradient Boosting and Random Forest. Keep the code simple. In addition to the three plots I have, it must also include a plot that shows relative importance of the variables

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