Python Scipy Jobs

15 were found based on your criteria {{|number:0 }} were found based on your criteria

show all
  • Hourly ({{ jobTypeController.getFacetCount("0")|number:0}})
  • Fixed Price ({{ jobTypeController.getFacetCount("1")|number:0}})
Fixed-Price - Intermediate ($$) - Est. Budget: $170 - Posted
hi there, I need modest hybrid (item-based) recommendation engine linking Users to Items in a database, which are mostly crawled with a small portion (<5%) crowdsourced. Marketplace [this is the main focus of the project] 1) User profile entered via i) registration ie preference/survey (item ranking). logged via fb/google accounts; ii) online behaviour [this is not the main focus of the project] 2) Items are classified with many attributes and assumed cleaned and structured. some but most expected to lack rankings by Users. Items are time-sensitive (perish over time) but can still be used for recommendation reference point. -> Match Users with Items. ie predict User's ranking on items
Skills: Python SciPy Django Ecommerce Platform Development Pandas
Hourly - Expert ($$$) - Est. Time: 1 to 3 months, Less than 10 hrs/week - Posted
We are doing some image analytics using Python and Open CV and that works well. While this can run happily on a server as a webservice we would like it to run within an app on iOS. One approach is to leave it in Python and use Kivy. The other is a straight port to C/C++ Your skills will include good familiarity with both Python and C/C++ with bonus points for understanding how you integrate C/C++ into iOS as a framework. Should we settle on the porting route the porting task will be ongoing as the final production version solidifies in the python prototype. You will be available now and quite probably one of the top 1% of hackers interested in working on a task that is the first extant tricorder.
Skills: Python SciPy C++ iOS Development
Fixed-Price - Intermediate ($$) - Est. Budget: $100 - Posted
Looking for excellent workers with experience in extracting large amounts of data from websites whereby the data is extracted and saved to a local file in your computer or to a database in table (spreadsheet attached) format. Pay is negotiable. Please see attachment for results needed. Seeking hard workers, dedicated, efficient, reliable, energetic, professional & motivated. We are looking for freelancers that have experience in Data Entry, Data Mining, Data Science, Data Scraping, Excel VBA, Microsoft Excel, Perl, Photo Editing, PhotoScape, PHP, Product management, Web Scraping, Data Scraping, Data Cleansing, Data Mining, Data Entry, Web / Internet Research MS Excel / Word Template Development, Database Administration, Document Processing, Administrative support.
Skills: Python SciPy Automation Data Entry Data mining
Hourly - Intermediate ($$) - Est. Time: Less than 1 week, Less than 10 hrs/week - Posted
Looking for experienced Python programmer to do occasional pair programming sessions and consulting chats. You will need excellent knowledge of Python 2.7, NumPy. Additional experience with image processing, machine learning is very welcome. Might eventually grow into serious projects.
Skills: Python SciPy Python Python Numpy
Fixed-Price - Expert ($$$) - Est. Budget: $300 - Posted
I need to implement methodology using Bayesian analysis on a state space model. It uses KALMAN filter to estimate likelihood and uses Bayesian analysis to maximixe pposterior density. Please apply if you have experience in using KALMAN filter, Bayesian analysis for estimating posterior density in Python. More details to be shared later
Skills: Python SciPy Econometrics Python Statistics
Fixed-Price - Expert ($$$) - Est. Budget: $100 - Posted
Project desciprtion: to figure out what are the used commands for a given user, and then see that suppose commands x occures and then commands y occures with x fir 10 times for most number of use. Then we can recommend that command y should follow x I would also like to use the word2vec in order to predicts target words given a source word. " Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text. It comes in two flavors, the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model. Algorithmically, these models are similar, except that CBOW predicts target words (e.g. 'mat') from source context words ('the cat sits on the'), while the skip-gram does the inverse and predicts source context-words from the target words. This inversion might seem like an arbitrary choice, but statistically it has the effect that CBOW smoothes over a lot of the distributional information (by treating an entire context as one observation). For the most part, this turns out to be a useful thing for smaller datasets. However, skip-gram treats each context-target pair as a new observation, and this tends to do better when we have larger datasets."
Skills: Python SciPy Machine learning Python
Hourly - Expert ($$$) - Est. Time: Less than 1 week, 10-30 hrs/week - Posted
We have some interesting data which we need to get insights from. As this data is something which we receive everyday, the delivery will be in the form of a Jupyter notebook, so it can be easily reused with new data coming in.
Skills: Python SciPy Pandas Python