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Machine Learning Jobs

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Hourly - Intermediate ($$) - Est. Time: Less than 1 month, 10-30 hrs/week - Posted
I have a large data set and I am trying to analysis the data using R application and do some visualization but I am facing a problems.
Skills: Machine learning Python R
Hourly - Expert ($$$) - Est. Time: More than 6 months, Less than 10 hrs/week - Posted
Our company is a startup and we are looking for an equity partner who we can also pay a fee for work or a combination. The individual will be knowlegeable in the above, able to review code, provide guidance to contractors, research issues, fix problems with code, run and implement code, Individual should have at least 15 hrs per week dedicated to this project. We are working on an interesting project that involves ecommerce, desktop software application development including sms features, navigation etc.
Skills: Machine learning Java Scala
Fixed-Price - Intermediate ($$) - Est. Budget: $800 - Posted
List of URLs: lakorn.guchill.com www.seriesubthai.tv www.kodhit.mobi cuptv.com www.startclip.com cn.upyim.com www.jengmak.com www.songdee.com th.hao123.com www.friv.com newsupdate.todayza.com diply.com tvshow.guchill.com www.subthaiseries.com www.tunwalai.com www.yumzap.com www2.adintrend.com devian.tubemate.home lakorn.guchill.com www.kodhit.mobi cuptv.com www.jengmak.com Step 1 Review the list of URL’s above, mine the top 1000 pages from that URL by using a crawler. Step 2 Extract terms from each of the these web pages that are mined Step 3 Determine if the terms from these web pages, match terms from the entertainment list or match elements from the news list. (Fill in the attached worksheet) Step 4 For each site create a new worksheet and repeat process
Skills: Machine learning Data Analytics Data scraping Web scraping
Fixed-Price - Intermediate ($$) - Est. Budget: $30 - Posted
I have 2 sets of data - a FIT and TEST data. I ran each one of them through the Linear Regression classifer in WEKA 3.6, under 3 methods: M5 method, Greedy Method, and No Attribute Selection. I also ran the sets under the Decision Stump classifier. I need to analyze the outputs between the different methods as well as compare the two sets to each other, based on the following criteria that is spit out: Correlation coefficient Mean absolute error Root mean squared error Relative absolute error Root relative squared error
Skills: Machine learning Data mining Statistics Weka
Hourly - Expert ($$$) - Est. Time: 1 to 3 months, 10-30 hrs/week - Posted
I have a clean dataset of around 200,000 observations over the last 15 years of certain financial events, with around around 10 features that can be used to predict returns. I have attached an ipython notebook with my work so far, and I'm looking for an expert to help me take this further. Note that because this is event data, instead of the normal random split of the dataset into training / testing, we need to only use historical data in the training set. If this works out well, there are many other similar datasets that I wish to analyze, and this will be a long term relationship with challenging, interesting and well compensated work. Skills: Machine learning (PCA, ANN, SVM, feature scaling, parameter optimization, ensemble algorithms, algorithm evaluation techniques), time series analysis, data visualization Packages: Python data analysis (ipython notebook, pandas, sklearn, seaborn / matplotlib) Must have strong verbal and written communication in English.
Skills: Machine learning Python
Fixed-Price - Intermediate ($$) - Est. Budget: $150 - Posted
I'd like to use Google's TensorFlow (deep learning neural network) to generate new content for me. I have about a 150 emails from a 10 year span. I'd like to use Google's Tensor Flow to generate/predict what these emails may sound like for the next 90 years. This is an experiment into utilizing neural networks. I understand that the information may be garbled. I do not expect a perfect response. I want something that is developed and coded well. I want to use the following batches of information: --> Existing batch of emails which have been condensed into a spreadsheet with certain topics and themes. Freelancer will have access to all emails and their content. --> RSS feeds from a single newspaper (with a filter for a particular topic/s). Freelancer will help identify good keywords for the particular project and use them to 'inform' the neural network. This will help it generate more accurate content. --> One wikipedia page listing content related to emails --> One multi sheet Spreadsheet showing incidents related to emails (not very extensive) What I need is a piece of software to connect to Google's TensorFlow to generate this content based upon all of this information. As I continue to get more emails (around 1 per month) and the wiki pages and other content sources update I'd like to be able to 'feed' it into Tensor flow to increase its accuracy. Somebody recently did this with episodes of Friends (http://www.thedailybeast.com/articles/2016/01/20/meet-the-robot-writing-friends-sequels.html) A good quote from the article was: "It's quite simple - It works by predicting the next letter to follow a given sequence of letters, and the predictions are determined by what it learned about language." Feel free to message me, we can discuss this in length. The freelancer is expected to put together a sensible structure for Tensorflow. His/her work will be reviewed by another coder who is familiar with neural networks/tensor flow.
Skills: Machine learning Calculus GitHub Python
Hourly - Intermediate ($$) - Est. Time: 1 to 3 months, Less than 10 hrs/week - Posted
YOU AND/OR YOUR COMPANY ARE… 1. experienced in advanced metrics: http://bit.ly/1PYLxei 2. experienced in machine learning and predictive sports betting analytics, ala: https://www.swishanalytics.com/ WE need an advisor/designer who can… A. look at the data we are currently scraping, and offer suggestions on how the data might be analyzed within our system to offer overviews and predictions similar in fashion to points 1 and 2 from above. B. assist in the creation of algorithms that our programmers will implement into our system. C. independently evaluate and test that the formulas and algorithms you have suggested and created for us, have successfully been implemented by our programmers into our system. D. be prepared to continue indefinitely with us in a cycle from A to C. WE DON’T NEED… -individuals and companies that can’t keep to a budget, or feel that deadlines are optional. We expect that the person(s) who are awarded this project will give clear and solid estimations on hours needed for completion of work, and will meet their deadlines without fail. -individuals and companies that don’t maintain regular and frequent contact with us. Failure to respond to a request for an update or other information within 24-48 hours, is grounds for termination from this project. -individuals and companies that want hours and weeks, “to run your data through our system, on our servers, to run tests to determine what might be the best possible outcome.” NO! You will only be serving in an advisory role as to what tests will be run on OUR system alone. We are absolutely open to any and all suggestions from you on how we might proceed, but we will not pay for testing periods outside of our system. IN SHORT… Look at our system and data; advise on how to implement advanced metrics and predictive analytics into the system; create the algorithms; check that the algorithms were correctly put in; make new suggestions on improvements and changes.
Skills: Machine learning Algorithm Development Analytics Data Analytics
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