Machine Learning Jobs

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Hourly - Intermediate ($$) - Est. Time: Less than 1 month, Less than 10 hrs/week - Posted
CANCER 3D Modeling from 2D DICOM Images ==================================== I am a student in a university with a health background and some basic information in Python. I am working in a cancer visualization and extraction project and looking for an experienced software programmer using python and have experience in medical imaging as DICOM images (digital imaging and communication in medicine).This project continues for one month and through it I want the programmer to make 3D reconstruction from 2D DICOM images. The program also makes extraction and segmentation of the tumor tissue from the background and segmentation of other tissues. Then it renders the 3D model of the extracted tumor. We need to use different kinds of algorithms as marching cube algorithm including interpolation and approximation for 3D reconstruction. Developer may use segmentation algorithms as K-means, region growing, threshold and the likes. I already started the work and I have online resources for DICOM images, I performed some scripts related to this work and downloaded some open-source of DICOM images software processing images as 3D slicer and imageJ. All of these I will provide the programmer to start his/her work. Program Requirements A program is needed to be written in Python. It will do the following: 1. Read sequence of DICOM .DCM images (2D) and render them in sequence and the sequence can be controlled with the mouse back and forth. (Already completed) 2. Segmenting and analyzing the 2D DICOM images and separate areas that are likely to be cancer (We will give the programmer some algorithms recommendations as well as the density that are likely to be cancer), separate cancer areas in new sequence of DICOM images, example: a. Original DICOM images (1.dcm, 2.dcm, 3.dcm, 4.dcm, 5.dcm, 6.dcm, 7.dcm, 8.dcm, 9.dcm, 10.dcm, 11.dcm, 12.dcm). b. The DICOM that contains cancer would be: (3.dcm, 4.dcm, 5.dcm, 11.dcm, 12.dcm). c. The following requirement in number (3), it will build the 3D model from the cancer DICOM images in (b) above. 3. Then build a 3D construction from the DICOM sequence. The 3D model should be controlled with degrees of depth (From skin to the deepest structure). (Completed partly) Figure 1: (2D DICOM image) Shows cancer in blue circle, the cancer can be analyzed according to several algorithms, some of them consider the brightness, some the circular shape, and some the density. The developer can use any algorithm that sees fits, to determine the cancer area in DICOM images.
Skills: Machine learning 3D Rendering Image Editing Image Processing
Hourly - Expert ($$$) - Est. Time: 3 to 6 months, Less than 10 hrs/week - Posted
We are in the plant business and would like to offer an optimized platform for other plant businesses online and offline. The goal is to collect data to create data sets and feed them into machine learning utilities. We need a solution that does the following Hadoop Ecosystem - create Hadoop environment to create a data engine to collect and distribute data sets - Collects data from consumer purchases/activity and online through API's and offline (a swipe card or bar code on app to assign user ID's ) - machine learning Vendor Applications The development of user applications that provide analytics to clients. The following technologies will be developed to support clients needs: Data Reporting Statistical Analysis Interactive Web Applications Enterprise Software The main goal is to develop a Big Data as a service solution for the Plant Industry Please give an overview of the solution - this will be a long-term development
Skills: Machine learning Apache Hive Big Data Cloudera
Fixed-Price - Intermediate ($$) - Est. Budget: $100 - Posted
The time limit is 5 days. The fixed payment is $100.00 I need someone to analyse Eight small datasets using convergent cross mapping (CCM). The purpose of the analysis to find the direction of causation. The Attachment below contains the Eight data sets presented in the form of Eight questions with multiple choice answers below. Analyse the data sets in the attached file with CCM and then circle the correct answer among the multiple choice answers provided below each question. There is only one correct answer for each question. Payment will only be given if all the questions are answered correctly.
Skills: Machine learning Data Science
Hourly - Expert ($$$) - Est. Time: More than 6 months, Less than 10 hrs/week - Posted
Hi, We have all the data available and can easily import this for you to aws machine learning, azure etc. We are looking for someone to use these tools to do a few things for us as a trial but starting with a recommendation engine in aws. Immediate start, dataset already in aws and pulled through to machine learning component so it really should be very simple as a trial before we move on to bigger pieces. Models we want to create are 1. Recommendation 2. Taste profiling 3. Churn Prediction 4. Replenishment Rates 5. What products to sell to who and when. Thanks, Ricky
Skills: Machine learning Data Science
Hourly - Expert ($$$) - Est. Time: More than 6 months, 10-30 hrs/week - Posted
We have a set up Python scripts that can build predictive models for sets of data. Currently the python script to produce predictions that are less than desirable, specifically for our regression module. We need somebody who understands Python programming, and can use machine learning libraries such as scikit-learn, numpy, and pandas, etc.
Skills: Machine learning Pandas Python Python Numpy
Hourly - Intermediate ($$) - Est. Time: Less than 1 month, Less than 10 hrs/week - Posted
Hi, I am looking for people with the following skill sets, if you are an expert in any of the following areas, please apply with your CV. 1. Robotics, simulation or experience with real robots, familiar with ROS, Gazebo suite of simulation software. 2. Computer vision: multiview geometry, structure from motion, human detection, object recognition, robust feature/object tracking, stereo vision, depth sensors computation (mono, stereo or TLF, IR), deep learning. 3. Visual SLAM, familiar with the latest SLAM algorithms, in-depth algorithmic level understanding, not just compiled some open source project
Skills: Machine learning Artificial Neural Networks OpenCV Robotics