Machine Learning Jobs

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Hourly - Intermediate ($$) - Est. Time: 1 to 3 months, Less than 10 hrs/week - Posted
I am looking for a command line tool that wraps at least one, and ideally a number of other packages to: Import from CSV Train model Validate that predictions work Predict empty cells Should do both multiple classification and regression. Should allow selection between multiple backends and modes. Should be able to select target column. Should generally autoinfer column type but should also allow explicit declaration. If you can make existing public packages do this reliably that's fine. During prediction, there should be two modes: In-place replace, in which empty cells get populated but everything else is valid. Or, accuracy mode, where everything is replaced. It should then be an option to add another column that states the real value and error level, if available. Multiple backend support should be inherent to the design. Vowpal Wabbit and MLPack are probably good backends, scikit-learn is fine but shouldn't be mandatory due to its fairly insane requirements (though I suppose we can just dockerize them).
Skills: Machine learning C++
Hourly - Entry Level ($) - Est. Time: Less than 1 week, 10-30 hrs/week - Posted
Hi, I have an educational data set of how students performed on various learning tests. One set of students was in a condition with one version of a learning game (physics). The other set had a different version. Three schools were run on this experiment. I have attached the data set here. Students were measured based upon their: -Pre/post test scores/gain scores -Engagement survey results -Number of trials within the game itself -Actions used within the game itself -Trial times on incorrect trials within the game -Trial times on a mini-game within the main game (differed across two conditions) -Spatial ability -Attentional ability -A few other specific metrics I would like the following completed in sci-kit learn using Python: I. Exploratory statistics (scatterplots, histograms, etc.) II. Training and Testing of dataset: GridsearchCV Classifiers: Logistic Regression, Multinomial Naive Bayes, Decision Tree, Random Forest, K-Nearest Neighbor, Support Vector Classifier. Model evaluation metric: accuracy,precision,recall,f1-score,mean-squared error. III. Clustering (k-means, KNN) students performance on the final test based on: -Pretest scores (high vs. low) -Spatial ability (high vs. low) -Attentional ability (high vs. low) -Perhaps game performance metrics (actions used, trials, time spent) This should not be more than a days worth of work, possibly less. I realize some of these analyses may not make sense, we can discuss together to refine the strategy. I would like the output and code for all these analyses. Thanks!
Skills: Machine learning Python Python Numpy Python SciPy
Fixed-Price - Entry Level ($) - Est. Budget: $10 - Posted
Suppose there is a 30X30 matrix. This will consider as input. The task will be make Spectral clustering on that graph (graph is undirected and represented by a matrix here). You have to include all the steps of spectral clustering at your code and finally find out the k-clusters from the graph. I have eclipse 3.8. The input will be at .csv format. The output will be the clusters of the sub graphs. Make you code simpole as I can run it on y system easily.
Skills: Machine learning Java
Fixed-Price - Expert ($$$) - Est. Budget: $2,500 - Posted
We are currently searching for a speech recognition expert who can help us building a prototype. The prototype should be capable of recognising language A, translating language A, streaming translated audio and text and vice versa in real time. The correct candidate should understand technologies such as speech recognition, audio translation, NLP, audio parsing and machine learning etc. This work is just to build the API's to enable real-time​ translation - no need for web development.
Skills: Machine learning Algorithms
Fixed-Price - Expert ($$$) - Est. Budget: $500 - Posted
• The main objective of our research is to develop an agent based knowledge discovery framework using a specific type of ontology based text mining. • The framework should improve the obtained results by finding new semantics rules when the agents extract knowledge. In addition semantic agents improve discovery accuracy and reducing the duration of mining the related information. • The framework should satisfy user needs on finding the resources that contain the desired knowledge. For that , I am looking for an experienced front end developer for one-time project. He must be experienced with big data technology , data analytic , machine learning , semantic and mining technologies and any other requirements related to the this area
Skills: Machine learning Big Data Data Analytics Data mining
Hourly - Entry Level ($) - Est. Time: More than 6 months, 10-30 hrs/week - Posted
We are looking for software developers to help us research and develop different solutions in the fields of computer vision and machine learning. Requirements: * strong C++ or Python skills * strong analytical thinking * familiarity with Linux systems (toolchains, make, cmake) * familiarity with OpenCV and/or other open-source computer vision/image processing/machine learning libraries Desirable Qualifications: * strong algorithmic design skills * strong scientific background (MSc/PhD)
Skills: Machine learning C++ Linux System Administration OpenCV
Fixed-Price - Intermediate ($$) - Est. Budget: $1,000 - Posted
Looking for a experienced data scientist with knowledge of Convolutional Neural Networks and Recurrent Neural Network, K-Means clustering. Also desirable if s/he has experience working with Deeplearning4j, wordvec, The project is to - Identify and extract text (short text) from an image (survey forms) - Extract meaning out of these texts - Map this text to predefined questions in database. - Identify answers fields and suggest location and related question of each field. - Train the model. Ideally the algorithms needs to be implemented in Java.
Skills: Machine learning Artificial Neural Networks Java
Hourly - Expert ($$$) - Est. Time: 1 to 3 months, 10-30 hrs/week - Posted
I have a very large set of 2d images - images of an animated humanoid's face from four different angles, and a few different animations for each angle. I would like to take all of these images and: *Build a form that allows the images to be categorized, so that they are associated with a Species type, a Faction type, and a Nation type. We can use additional tags as needed to accomplish the task, based on your expert recommendation. *Write a program that can "diagnose" another input similar to the other 2d images in the set, and tell me which Species/Factions/Nations seem to fit best. *Write a program that can draw a new image based on a user selecting defined inputs for Species/Faction/Nation. This program should also allow for editing of the image based on aesthetic features, changing (for example) eye color, hair color, hair style, and other aesthetic details. Sample image attached. There might be 10,000 or more of these.
Skills: Machine learning 2D Animation Image Editing Image Processing
Hourly - Expert ($$$) - Est. Time: Less than 1 week, Less than 10 hrs/week - Posted
Hello. I have a DIGITS server running. I've built a dataset of 400 images of 3 different types of sunglasses. I'm a software engineer of 15 years but have only been doing deep learning model training for 1 week! :) I'm trying to get image classification of 3 types of sunglasses going. I've trained many models with GoogleNet but am sorta making educated guesses at parameters. I'd like someone to consult for a couple of hours taking a look at my dataset, helping me understand how to choose good parameters and what are good augmentation filters to apply to my dataset to generate more images. The best model I've been able to generate thus far has about 75% accuracy on my validation tests. It must get better though. If you feel like you could help me learn how to use DIGITS to create better models, then I'm looking for you!!
Skills: Machine learning Artificial Neural Networks