Python Numpy Job Cost Overview
Typical total cost of oDesk Python Numpy projects based on completed and fixed-price jobs.
oDesk Python Numpy Jobs Completed Quarterly
On average, 13 Python Numpy projects are completed every quarter on oDesk.
Time to Complete oDesk Python Numpy Jobs
Time needed to complete a Python Numpy project on oDesk.
Average Python Numpy Freelancer Feedback Score
Python Numpy oDesk freelancers typically receive a client rating of 4.78.
I am a computer vision expert with a PhD in automated video analysis. I have a proud record of developing robust computer vision and machine learning solutions, and draw on 19 years of R&D, and management experience in automated video analysis: * scene analysis, * background modeling, * motion estimation, * camera calibration, * automatic geo-registration, * object detection, tracking, and classification, * event detection, * context and model learning: supervised, unsupervised and semi-supervised Large recent projects * bridged the semantic gap between RGB pixels and textual content summaries of video content, * integrated visual data with GIS and web resources to automatically geo-locate images, * developed and field tested autonomous rapidly-deployable video analysis nodes, comprising 11MP cameras, WiFi/3G/4G, low-power Intel PC board, Li-ion batteries, that operate indefinitely powered by a 60W flexible solar charger, and * visually estimate heart rate from webcams I'm happy to review your project and help you size your work
I'm a senior Python developer with experience both in web and scientific scopes. I have a degree in Computer Enginnering from Cordoba national University, Argentina. https://mgaitan.github.io/en/about.html
Artificial Intelligence(e.g. natural language processing, computer vision, machine learning), Embedded Systems(microcontrollers, development boards) and Robotics(both automated and teleoperated) are my key areas of expertise. I have worked on those fields as a part of multi-disciplinary team and as an individual. Notable among them are, competing in a robotics competition organized by NASA and developing a novel Optical Character Recognition system for an alphabet. My involvement with open source technologies has habituated me to work with legacy code, writing comprehensive documentation and code reuse to avoid reinventing the wheel and to save precious time.
I'm a theoretically-oriented PhD student in Optics, and I develop high-performance parallel applications. My skills and tools are: - Fortran and C, Python 2.x; - BLAS/LAPACK routines from Intel MKL, AMD ACML or ATLAS; - Sparse solvers from PETSc and SLEPc: eigenvalue problems, linear equations solution; - hdf5 library: powerful input/output standard; - Matlab | GNU Octave professional use; - Linux server & desktop administration (including deb & rpm based) + hpc cluster support; I have practical experience with the numerical solution of large-scale sparse eigenvalue problems (greater the then 100,000), and I'm used to OpenMP parallelization scheme. I also have strong research background in quantum chemistry, physics and material science. And, of course, all my reports are made using LaTeX.
I'm friendly and dedicated to finishing what I start. Just like you, I am a busy person. I like to work efficiently both to maximize quality and to minimize wasted time. I use python, R, Matlab, and C/C++ as languages, I use machine learning algorithms with python for large data analysis problems. I have a B.S. in applied mathematics and am getting ready to start a graduate program in mathematics and computer science.