Tips and Tricks.
I need help in a research paper writing which is related to Machine Learning. The project is about ECG Signals Classification in MATLAB. Bid with a proper proposal please. I will share more details with the suitable persons. Thanks For more details about project have a look at [login to view URL]
We have a long list of company names with and without company form, different writings, etc. We are looking for someone who can "clean" this data with OpenRefine or any other tool of your choice. I would need a quote per 5k Data and per 100k Data (please mention these amounts in your application !)
2 compartmental drug model data analysis for a unknown drug. I will give simulated data and need to calculate the dose, rate of clearance, volume of distribution etc...
We are working on creating an artificial intelligence based real estate platform. This platform will be primarily based on IDX/DDF/VOW to synthesize high volumes of data and provide investment-oriented graphs and information to premium clients. Require assistance of someone with extensive experience in real estate platform development and understands AI / Big Data / Machine learning.
I need help to make all possible combination of search queries to be fast when querying my data. I have normalized my data structure as much as possible, on my opinion, so it needs the least amount of indexes possible. I also have some ideas of indexing strategies we could try to achieve the requirement. I'm open and willing to change the data structure, or the way the query is done, or anything else as needed to achieve the best possible strategy for indexing data and make all searches very fast. My current DB is MongoDB, so preferably to find the best strategy for it (although I'm open to change DB if really worth it). The estimated amount of records we will have on production environment is about 8 millions. I provide attached an example of the JSON data with 1 record as "[login to view URL]", just to give you an idea of the current data structure. My indexing strategy idea and explanation around it is in the attached file "[login to view URL]".
The way we work with other members of the team at this preliminary stage is by writing blog articles that are the result of that specific topic. Every article is 1500 word length and in comprises the topics For example your first topic will be : "Assessing visitor intent by analyzing 1st, 2nd, 3rd party " data in a B2B website the length of the article will be 1500W the content should properly tagged for references and resources : minimum 4 to 6 links the content must have simple diagrams explaining the content (this will be enhanced by our graphic artist > simple sketches would work) Min. 8 (diagrams, charts, ...) it can be from other sources as well. Google is very much sensitive to perjuries so content should be purely self written.
We have survey data + SQL data that needs to be analyzed to surface insights and trends that we can use in marketing, e.g. "XX% of customers saw YY% increase in..."
data modelling, data dictionaries, and creating and enforcing standards and good practise around data management. Ideally in relation to Big Data solutions. Any of the following bigdata platforms(Hadoop, Spark, Impala, Presto, Airflow, Hive, HBase, Kaftka, Sentry)
We need to find data and/or software along with a person who can be given an address on a map to receive a data service from a close by antenna. We want to be able to define an address or group of addresses and it to show us on a map (like a heatmap) ALL the worst to best options to place a tower for install.
Hello I need some clarification & help with questions on the following topics. Topics: Computational Complexity (Turing Machines) Greedy Algorthms(Optimal Substructure,Greedy Choice Property,dynamic vs greedy algorithm) Master Theorem Loop Invariants(Bubble Sort) Activity Selection Problems Dynamic Programming Safe Edge(Spanning tree) Prims Algorithim(Min spanning tree) Dijkstra Algorithim Please Note the questions i have are not a Programming based
INTRODUCTION One of the most critical factors in customer relationship management that directly impacts a company’s long-term profitability is customer attrition. When a company can better predict if a customer is likely to cut ties, it can take a more targeted approach to mitigate customer turnover. In this task, you will use Python, SAS, or R to analyze data for XYZ company and create a data mining report in a word processor (e.g., Microsoft Word). You will create visual representations throughout the submission to show each step of your work and to visually represent the findings of your data analysis. All algorithms and visual representations used need to be captured (either in tables within the word document or with screen shots added into the word document) and should be submitted as part of your document for final submission A separate Excel (.xls or .xlsx) document of the cleaned data should be submitted along with the written aspects of the data mining report. SCENARIO You are an analyst for XYZ company that is concerned about the number of customers leaving their landline business for cable competitors. The company needs to know which customers are leaving and attempt to mitigate continued customer loss. You have been asked to analyze customer data to identify why customers are leaving and potential indicators to explain why those customers are leaving so the company can make an informed plan to mitigate further loss. REQUIREMENTS ....
We need a data science project designed and deployed that can do the following type of data: 1) Find areas, such as zip codes, that have input defined speed broadband or other internet connections speeds. 2) Find areas that have a imputed amount of broadband providers. 3) Find cell towers in a defined area and map 4) Find water towers in a defined area and map 5) Find, if possible, areas with highest complaints for broadband 6) Find ideal location coordinates per defined area where to install towers to reach maximum distance to a second receptor based on terrain topology to show best install locations 7) Show population for areas for all data above 8) Show various census data for areas
We have a large data with inventory, raw materials and issues etc. Need to have good analytics and reports to take good actionable intelligence... Engagement could be long term for the capable... In coimbatore personal are advantages
I need a Stata regression performed of Eurostat data for health issues during the Great Recession and to show the following variables: So basically the list I provided now. I think it's in line with what we discussed, using the time between physician visits as the main variable. The as for the control variables, if you find something that you find odd/unnecessary you have full freedom to change/add. Time between physician visits (basically sticking to your idea) -what you said regarding adding time dimension to health, with the assumption that health deteriorates if left to itself. This variable being (in my view) a good proxy for something rather subjectively defiend such as personal health. Healthcare expenditure (think I missed this before) -as we wanted to gauge the time effect of neglecting physician, and its impact. Time stayed in hospital -measuring severity of hospitalization (especially in socialistic countries that generally discharge as soon as possible to cut medical expense). Also opens for the possibility to test whether hospitalization during increases with neglecting ones own health. Alcohol consumption -risky behavior that can proxy for behavior people rarely admit, or have a hard time defining (depressions, some stress etc) Tobacco consumption -similar to alcohol but tobacco consumption (by personal observation), much more often represent pure stress related tendencies Medicine consumption -quite self explanatory Obesity by BMI -not the best measure but it does apply to alot of the population, as a good measure for physical health. Physical activity -By personal experience periods with alot of work, school etc. Training progress is the best, productive people find time. By experience physical activity declines with significantly increased free time. Gender (unsure about this one) -Often when doing population wide studies this I feel gender is often shoehorned in due to popular demand. But here as the study also seeks to examine behavior I do feel it can add something to the model as a whole. GDP -I think this is the simplest way to track and monitor business cycles. Unemployment duration -Factor for stress and depression (especially what I mentioned earlier regarding at least Swedens social safety net). I think this is more important here than a simple unemployment statistic. Inflation -nothing much to specify here Productivity -Factoring in and controlling for economic progress, not just growth. Household expenditure -Gauging the severity of being laid off. I.e. difference in income when employed vs unemplyed. Working time -By assumption people should work more during a boom, but again we want to factor out cases where more time spent working=more work related issues.
We are currently working on "A Discrete-Event Simulation Approach to Project the Prison Population in the UK over the next 10 years". All the data is currently available we need someone with experience in simulation model platforms such as: InsightMaker. The main purpose is to simulate the prison population over the next 10 years and compare it to the current certified normal accommodation (CNA) and to the maximum capacity This will allow to see the likelihood of prisons being overcrowded and also allow a view of if a situation of not having the capacity to deal with the number of prisoners in the system will arise. Useful Knowledge required: System Dynamics, Agent Basednand Discrete Event (Process‐centric) modeling. The project is quite complex and ita report writing. For more information please get in touch. only if you have knowledge on the methods and platforms stated above. Thanks! ===================================== Literature Review. Give a short critical literature review on simulation applied to the chosen problem, or class of problems. (min 5 different papers) 1. Problem & System Description. Project goal. Choice of performance measures. Include a system sketch or flow diagram. What assumptions are you making about the system? Describe relationships between key variables, if any. Describe the pros and cons of various types of simulation (DES, Monte- Carlo/spreadsheet, ABS, SD) in relation to your problem. 2. Key Data. Data sources: How were data collected? List major assumptions. Show the fitted distributions, including their p-values. 3. Insight Maker.) Correct usage of modules; layout; use of animation. Include a printout of the base case model;. Originality 4. Experimentation & Output Analysis. Describe experiments that you ran with the model. Organize/summarize output in at most 3 pages using graphs, tables. Most of the dat needed for the project can be found on the [login to view URL] files attached freelancer needs to have experience in simulation model
Need python script to code. You have to code a script based on a research paper. I uploaded the research paper as photos. Task - Derived the weight table and calculate probabilities for each customer type using those weights. And also need the accuracy score. This will be a easy task , who know what they are doing I will provide the survey data for the selected person
You need to create an ESRI Network dataset for analysis into ArcMap. The project is quite urgent and the bidder must be well versed in network analysis. Site: Surat, Gujarat, India. Requirements of Dataset: National and State Highways, Arterial and SubArterial Roads, Some Distributor and Local Roads in vicinity to objects in the files which will be sent.
Requirements Looking for data scientist with past experience in projects that sole deal with user intent mining. 1. Please list your past experience in such project 2. What was your role? 3. Attach a quick process showing how are going to build predictive analytics using user intent descriptive analysis And finally how would you apply MLL to the process? Responsibilities for Data Scientist • Develop custom data models and algorithms to apply to data sets. • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes. • Develop processes and tools to monitor and analyze model performance and data accuracy. Qualifications for Data Scientist • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. • Experience working with and creating data architectures. • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. • Coding knowledge and experience with several languages: C, C++, Java, • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. • Experience querying databases and using statistical computer languages: R, Python, SLQ, etc. • Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. • Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc. • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
I mean briefly Step 3: Machine Learning Techniques Deadline: TBA Outcome: Blog, Github and PDF - Buiding a Model with a ML technique (decision tree vs.) - Verify your Model (it does not have to be successful) - Use at least two of Models and describe which one performs better and why. Try to describe which features works best for each ML Technique.
Hi, good to have tensorflow skill. [login to view URL] We need autoprocessing.. Requirement - - Any machine learning platform is fine. I will provide details to right candiate. Only those guy who have expierience in machine learning in audio processing can apply.
We are looking for software and hardware developers that can work on a music streaming service that also has a a hardware that recognizes a song listed on our database. Basically think of this as a shazam hardware but will only recognize music listed on our database. We need a team, that can work on the mobile application, the desktop version and back end. We are also looking for a good hardware team that work on tying the software in with the hardware. [login to view URL]
I Need someone who is expert in python and deep learning, CNN, Google collab, to run my python code for me and do a small powerpoint presentation of the output. I already have the codes and datasets and everything. Thx
We are a fitness studio, with 80 instructors, and want to make recommendations to new riders of which instructors they'll like best. Based on past data of frequency that riders go to different instructors, I want to have data analyzed for each instructor to find similarities with behaviours of instructors. Similar to Amazon, we want to recommend Instructors that rider may like "Those who had a class with Stacy, also liked these four other instructors". This should be presented in a report with each instructors name, and the probability of riders to go to each of our other instructors based on past data. Example: Clients who went to Stacy's class are: 95% likely to go to "Jim" 87% Likely to go to " Rob" 75% Likely to go to "Stephanie" etc. I look forward to working with you.
I need help in a research paper writing which is related to Machine Learning. The project is about ECG Signals Classification in MATLAB. Bid with a proper proposal please. I will share more details with the suitable persons. Thanks
I have gathered tourists data for over 6 months now. I have already done some mining techniques on it for some case generations. Need some more analytics and evaluation. Also want the final document in professional format.
Imagine you are covering the United States with cell phone towers. Each tower has a range of 100 miles. The goal of this project is to identify where you will put each tower, trying to cover the country with as few towers as possible. In other words, we want to identify the fewest number of United States cities that will cover the continental United States (when each are given a radius of 100 miles). This may not straightforward right away - I suggest you refer to either the attached screenshot or Google doc for a visual: [login to view URL] We are basically creating a mesh of geospatial coordinates within 100 miles of each other to envelope the continental United States, For each coordinate, we are looking for a city name, state, and latitude and longitude information. For example: New York, NY, 40.6974881,-73.979681 Philadelphia, PA, 40.1937313,-75.0102984 Atlantic City, NJ, 39.3766056,-74.4879281 Cites may overlap - but the goal is to identify the fewest number of cities as possible - so overlapping is not preferred. In order to be considered for this project you must demonstrate a working understanding of the problem as defined above. Please provide a summary of your approach, including tools you will use, how you will verify your work, etc...
I'm looking to somebody with experience creating algorithms to help me create a quick software proposal with.
I need you to develop some software for me. I would like this software to be developed for Windows using SQL.
I need a Machine learning expert for my multiple projects. If you have knowledge please bid. Details will be shared in message with the freelancers. Its a small job .
Data Frame1: EmpNo EmpName Salary E123 Tom 2000 E124 RAM 2000 E125 TAM 2000 E126 SAM 2000 E124 RAM 4000 E126 SAM 6000 E125 TAM 9000 E123 Tom1 4000 Transform this DataFrame to DataFrame2: EmpNo EmpName Salary rownum E123 Tom 2000 1 E124 RAM 2000 1 E125 TAM 2000 1 E126 SAM 2000 1 E126 SAM1 5000 2 E124 RAM 4000 2 E126 SAM 6000 3 E125 TAM 9000 2 E123 Tom1 4000 2 Here is the summary: -- Duplicate EMpnos should be indexed(as shown in the rownum column) -- The order of index should be based on salary. -- Need All of the below approaches -- Should be optimized and should be runnable on a cluster. 1. Using RDD(a. using SparkContext, [login to view URL]) 2. Using DataFrame(a. using SparkContext, [login to view URL]) 3. Using DataSet(a. using SparkContext, [login to view URL]) DataFrame Operations should contain both . notation and sql notation. Action Items: 1) Development 2) Testing 3) Demo 4) Any corrections/small enhancements(if required)
If you have any of the below skills feel free to contact me. You do not need to have all the 3 skills. But make sure you do not apply for this job it you are not an expert in at least one of these language. If you think, you are an expert in anyone of the below language then do not hesitate to contact me. 1) PySpark 2)Python ( NUMPY, SCIPY, PANDAS, SCIKIT-LEARN) 3) SQL Programming skills 4) Dockers and Kubernetes
We have a number of datasets available and are looking to train a model(currently available), in order to most accurately depict dataset nuances and strengths.