Hi I am looking for help in machine learning using python programming. I have a dataset of parkinsons disease and the features extracted, so using them we need to classify if the patient is taking medication or not. The Multilevel perceptron in neural networks is a good solution, but before that as there are 9 features we have to know which 2 features
Team, I trust you are well. I am looking to obtain information on two separate items, both related to the skill of web parsing. The first dataset required is for Auction results of properties, in particular these two websites have auction results of commercial properties and i require all the relevant details in particular sale price, sale
I have a dataset of nodes and links that change every year (7 years). I need to created an animation of this evolving network using processing. The animation has to be able to read any csv file with network information.
The Company is Doohikey Designs we product specialty wood products for the quilting market. We are now having our products made in the USA...need to find a team of artist to paint and finish our products. You can check our website at [url removed, login to view] We have 5 products all made of wood. We need them the binding babies items painted with faces.
...and an auto-generated English sentence that corresponds to the formula. My simplification script got lost, but here are a few Python snippets you can use to easily access the data you want. import re line = [a line from Lore KB] KB_LINE_MATCH = "(:s (d+) ([^()]+) ((.+)) "(.+)"" m = [url removed, login to view](KB_LINE_MATCH, line) weight = int(...
I have a dataset of Indian MFIs for 2016 with 2 inputs and 3 outputs already collected. [url removed, login to view] task is to run DEA using CCR model with CRS 2-stage with 21 different specifications of inputs and outputs (all possible combinations). I want to see the raw results from whatever software that was used (Stata, Matlab etc) 2. I then want to run a principle
...(specialization/generalization from WordNet and LoreKB) or how to make a system that predicts the specialization/generalization of words, such as training a simple classifier from data. The format that you write it in can be anything that is easy to access and fully captures the information. In general, we would probably want them in EL or ULF universal
I created a website which outputs some data into two types of XML files. One is a field by field export, the other one is more preformatted fields type. You get DTD and a sample XML for each type. Your task is to create two Adobe InDesign template files, one for each type. They must be prepared for "ready-to-use", means: When loaded and XML is
Need: A Story line with 5-6 dashboards on Tableau. Dataset: 2 csv based (supplied) + joining with US zip code longitude latitude (not supplied) Essentials:deliverable by 13th Dec EOD, some analysis but now much, great visualization charts & maps (basic histograms will not do), Interactive dashboard to tell a story in 10 mins and emphasize on asthetics
For a smaal research project I need a python script written what uses tensorflow to create a small neural network which can is trained on this dataset: [url removed, login to view] and can recognise handwriting. It should look somewhat like this: import tensorflow as tf from [url removed, login to view] import input_data
Go to the [url removed, login to view] and generate MD5 hash for your name. Example: MD5("Art") = "978D7D6BDE930F0FA9615627A15B2FC1" Divide the MD5 hash on 4 substrings each of the length 8 First part of the hash when divided by 7FFFFFFF gives you an intersept, β₀, of your population regression modelSecond part of the hash when divided by 7FFFFFFF gives you a slop...
What are the primary drivers of ER utilization indicated in the dataset? What action do you recommend the carrier take to discourage unfavorable utilization? Use any tools you feel appropriate to execute your analysis, but it would help for us to know which tools you used in your approach.
I have a l...attached sheet. 2. The list has around 16000 entries, but many of them are duplicates. You should be able to identify these duplicates and get back to me with the final dataset with unique entries only. This is the first in a series of assignments. A good candidate will have access to opportunities in the future as well. Thanks
...the service rows. 4) The only data your work needs to be responsible for is to enter Services name (complete list) to each unique model number. An example of the completed view output is located in the "Sample Complete" sheet for you to view and see the completed outcome. 5) Column "post_title" is where this data is finally brought together and
Looking for a large relational dataset which can be one of those open datasets but want them to be relational data model so the tables are connected either normalized or denormalized. We need some FRS, and use cases that can be derived out of these datasets, something like ETL, and BI reporting. Requirement: Industries preferred : (Aviation,
...of multiple variables. We have more than 270 predictors and more than 8.000 row to predict the score. MSE will be the evualuation method with a minumun of 10% of test dataset sample. Final machine learning model have to be less than 4.5 of MSE in total rows, and less than 10 for each player position (goalkeeper, defender, midfielder, striker)
...and create a webpage with creative graphic and texting input. Hosting has no CMS this time, binding for me not required, but possible to install. The Language is English and includes 6-8 Pages. The focus is to visualization definition “Consultant”, “Business Startup” and “Network”. Analogously to create new business and network, ...