Python Numpy Jobs

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Fixed-Price - Intermediate ($$) - Est. Budget: $250 - Posted
Given NBA season dataset 2014-2015, tell me what patterns can be found and features we can extract, so that we can predict the final scores of the 2015-2016 dataset. Tasks: - Based on the 2014-2015 NBA season dataset provided, create data visualizations on the patterns found (High Priority). Visuals may be outputted in graphics or html. - Discuss how we can make use of the patterns / features to predict the next season. - Predict the final scores of the following season based on the initial model. This job is an ongoing project, and would bring in more work very soon. The priority is to build an initial model, and create visuals based on the initial dataset. I need someone who can do the visuals in one day max - or at least provide the visuals output.
Skills: Python Numpy d3.js Data Analytics Data Visualization
Hourly - Expert ($$$) - 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: Python Numpy Machine learning Pandas Python
Fixed-Price - Entry Level ($) - Est. Budget: $10 - Posted
Hey, I am new in the Docker-Universum... I need a Dockerfile for Sympy-Gamma. It shoud be a very easy Thing but i actually not have the time to read into Docker. Start with this container: I can use docker build and Docker run commands ;) Have a nice Day Christian
Skills: Python Numpy Docker Python Python SciPy
Fixed-Price - Expert ($$$) - Est. Budget: $500 - Posted
In need of python developer. Project I expect is 3-5 days in duration. I would like to connect an open source software (zipline) to 2 datasets from quandl, so I can run custom code on top of it (custom code already developed). Open Source Software: Dataset 1: Dataset 2: Datasets will be provided to you. Objective: Enable use of quandl data (stock data / fundamental data) in zipline algorithm via the Pipeline API Requirements: 1. Use stock data from quandl and connect via a data bundle to zipline, and then a sample algorithm 2. Load fundamental data from quandl into zipline sample algorithm 3. Leverage stock data and fundamental data in sample algorithm, where data from both sources is used via the Pipeline API a. Ex: reference AAPL stock symbol, and AAPL’s revenue, and AAPL's Dividend Yield through the pipeline API 4. Deliver a zipline sample algorithm that uses 10 columns of data from the quandl fundamental data and the stock data from quandl in a file for testing to ensure the algorithm works. Also include a pipeline filter in the sample of code for the fundamental data. 5. Throughout code, include comments, so the code can be followed Note: Algorithm should include buying and selling of 1 security using the pipeline data daily – security could be random – profitability of algorithm is not important.
Skills: Python Numpy Python
Fixed-Price - Intermediate ($$) - Est. Budget: $300 - Posted
You’ll be responsible for doing the following for the Project: - Building, evaluating, and assessing different Machine Learning Algorithms or processes, such as - Supervised Learning - Unsupervised Learning - Reinforcement Learning. - Build Scalable Deep Learning Algorithms using low-level code to crunch massive datasets. - Conducting ad-hoc data analysis. - Perform ad-hoc duties as required by supervisor.
Skills: Python Numpy Data Analytics Data Visualization Machine learning
Hourly - Expert ($$$) - Est. Time: 1 to 3 months, 10-30 hrs/week - Posted
I have raw exports from a Wordpress website, which can be shared as a 350MB zip file containing XML files. The XML files contain structured data representing the news stories on our website, including: Headline, Publication Date, Author, Article Content. We are trying to understand a few different things about the content on our website. 1. What topics do our journalists write about? 2. What topics do our journalists write about with authority? 3. How well does our site taxonomy describe or organize our content? 4. Based on an analysis of the stories, can we do a better job of related our content? I am looking for someone to conduct an analysis of our content. The right candidate will be able to: * Identify 10-20 topics or subjects that are discussed across a number of articles; determine the topics that the website has "topic authority" (we can discuss what constitutes a "topic" before we begin, and what constitutes "authority") * Generate a list of articles that discuss each of these topics * Analyze topic authority as a function of Author and Content Category of the website (for example, the website has a category "News & Politics" as well as "Business & Technology, etc... What topics do are covered by those categories?) You should be capable of providing the source code and outputs in the form of CSV files and plots (generated using the tool of your choice, but ideally R, Python or an open-source solution).
Skills: Python Numpy Python Python SciPy R
Fixed-Price - Expert ($$$) - Est. Budget: $50 - Posted
This is a relatively simple job. Need a python script that will take an aliExpress URL, and output the price and other details. Good commenting and clean coding practices required. The input will be a comma delimited csv file with the following columns: A. Reference Code B. Type C. Aliexpress URL The output will also be a comma delimited csv file, and for each row in the input, should have the following: A. Reference Code (passed from input) B. Type (passed from input) C. Aliexpress item Title (Scraped) D. Seller Name (Scraped) E. Price/lot (Scraped) F. Qty/lot (Scraped) G. Price/pc (Calculated E/F) The Quantity String is for items that have a "size" selection. Attached is a sample input file, and a sample expected output file. Errors should also be noted in the output csv, or in a separate log.
Skills: Python Numpy Data mining Python Web scraping
Hourly - Intermediate ($$) - Est. Time: 1 to 3 months, 10-30 hrs/week - Posted
Looking for an individual with a background in biomedical engineering, electrical engineering, or physics who has a firm grasp manipulating and analyzing continuous time-series data. Working with the project manager, this project requires planning, developing, and implementing a physiological data analysis scheme comprising of signal processing and synchronization, feature engineering, and probabilistic classification analysis using machine learning methods in MATLAB and/or Python.
Skills: Python Numpy Data Engineering Machine learning MATLAB