# Vowpal wabbit regression jobs

We are looking for Frontend Web Developer who can work for our company proje...implementation.
Core Responsibilities:
Develop new user-facing features
Build reusable code and libraries for future use
Document work to enable other developers to build on progress
Work with back-end developers to integrate front-facing features with APIs
Optimize application for maximum speed, scalability, and SEO
Develop automation test scripts for quality assurance and **regression** testing
Collaborate with other team members and stakeholders
Responsible for the code reviews & managing the integrity of the production code base i.e. Auditing & managing the production code base / code repository
Management of the Front End – ensuring documentation and st...

...
B. Next step, we will need to perform cross-validation by perform partitioning our data.
Use Analytic Solver’s standard data partition command to partition the data into a
training set (with 50% of the observations), validation set (with 30% of the
observations), and test set (with 20% of the observations) using the default seed of
12345. (1 point)
C. Perform discriminant analysis, logistic **regression**, k-nearest neighbor (with
normalized inputs), single classification tree (with normalized inputs and at least 4
observations per terminal node), and manual neural network (use normalized inputs
and a single hidden layer with 3 nodes) to create a classifier for this data. How
accurate is this procedure on the training, validation, and test data sets? (1 point)....

We own a retail family business in the textile industry and we have our e-commerce website. We would like to create some analysis and automated dashboards. We have our data in the SSMS database, so you should know MS SQL.
You can make th...and we have our e-commerce website. We would like to create some analysis and automated dashboards. We have our data in the SSMS database, so you should know MS SQL.
You can make the dashboard in any tool you like, but then you will have to demonstrate how to use it. We have an in-house team.
Moreover, we need time-series forecasting of our products to help our inventory management. Simple **regression** will do, but for all products and in a graphical way so that we can interpret it.
We will have a bigger digital transformation project, but f...

I am finishing up my Research Paper and I am having trouble with the multinomial logistic **regression**. I am analyzing demographic factors, police contact, experiences of discrimination, and experiences of victimization and how this affects trust and confidence in police officers. I have an SPSS file already completed with the survey with weights and just having trouble with the actual analysis.

In this application you will use daily data on your company returns together with the S&P500 retur...dincludingFebruary28th2020. Denote this sample size T1. Set the forecast (evaluation) period to be the remaining observations from March 1st, 2020 to the last observation. There are T − T1 observations in this forecast period. Use the following methods to choose and estimate suitable forecasting models using the in-sample data only:
(i) 30 days sample mean for that asset
(ii) A Reg-AR(1): a **regression** with the lag 1 market index return added to a an AR(1) model for your company return.
(iii) A CAPM Model for the excess returns on your company stock.
I have further details as we have some work done on this project, please leave your bids so we can discuss this in detail.
...

I need some one to carry out financial programing by using python so that I can use that analysis.
I already have a given dataset with European stocks.
I need to clean that dataset to my needs and carry out a CAPM **regression**, Fama French **regression**, and Fama Macbeth **regression** with portfolio returns.
The program should be written as an anaconda file.

The first model is logistic **regression**, and the second model is decision tree. The target/response variable is Attrition and the evaluation metric is accuracy
1. Describe and explain both models (i.e., methodology) in a short paragraph.
2. Show the key stages of the process of how you implement both models in R.
3. Select the best model and then discuss in detail and summarise the business insights provided. For example, which variables/features are important in prediction? What types of customers are more likely to churn? What do you think might be the reasons behind the findings? Your analysis needs to be reasonable, and you could include some business theories or evidence to justify your statements along with the empirical findings from the provided data.

I have done some EDA and modeling using some economic data both globally and limited to Asia
I need someone who can take the output and provide me with written analysis
You should expect to write about EDA, PCA, Panel **Regression**, Decision Tree, Random Forest and neural network and I might add a clustering technique
payment can be per page, per hour or as a fixed price
providing samples of similar analysis is required to be shortlisted

Hi Gary N., I am looking for some stats assistance with a small scale retrospect cohort study. It’s a low impact medical study. Results are reporting RRR and logistic **regression**. Stats is not my strong point so I need some support with this.
Would you be available?

Deadline: next 4-5 days
Looking for help running a multi-factor **regression** analysis.
The analysis will consist of an event study, to observe the price movements of the stocks around the time of their deletion from the S&P 500 Index. However, rather than using raw returns for abnormal returns, I will calculate the abnormal return for each security in the final deletions sample using a modified market model (to be provided)
I will run a **regression** for each of the deleted securities using data for the observed dependent variables starting 253 days before the AD+1 through 253 days following that date. I will use AD+1 as the “event” date since deletions are usually occurring after market close making AD+1 the actual date where markets can react to the news. That i...

I am in need of a machine learning expert to help me prepare my model based on requirement. It is a **regression** problem and i would like to fit the model into Linear , polynomial , ridge , lasso , random forsest and apply other boosting techniques and finally ANN.
I need clean code to fit my requirement.
Thank you

...DART-MX8M SOM (based on NXP Quad 1.5GHz ARM Cortex-A53 plus 266MHz Cortex-M4) and/or nanoPi boards (Arm Cortex CPU)
⦁ iOS app (Apple) development for iPhones (Swift).
⦁ Troubleshoot hardware/software
⦁ Assist in troubleshooting and testing of firmware.
⦁ Reviewing previously written code to give feedback on code design, proper documentation, and update documentation.
⦁ Develop (automated) **regression** tests
⦁ WiFi and Bluetooth low level control and debug.
⦁ SSD, PCI, serial ports, DAC, ADCs interfaces.
Qualifications/Skills
⦁ Five of more years of firmware development
⦁ Demonstrated knowledge of firmware/software release and documentation
⦁ Linux programming, microprocessor programming, C, C++
⦁ Computer science or software development degree
⦁ Two or more years of experience in...

I am looking an SDET who can build automated **regression** suite to be created and make it running successfully

Need to confirm my attempts to use SAS and STATA for simple linear **regression** analysis, 2 sample t test, case control, ANCOVA. I'm learning technique, so small data sets - 10 to 20 data points.

...negatively correlated, or uncorrelated? Explain why your answer would be expected.
Change your scatter plot to show the points for each year in a different color. Does the relationship between the two variable change over time?
Do a linear **regression** for these two variables. How much variability does the line explain?
The plot above does not adjust for inflation. You can adjust the price of a pack of cigarettes for inflation by dividing the avgprs variable by the cpi variable. Create an adjusted price for each row, then re-do your scatter plot and linear **regression** using this adjusted price.
Create a data frame with just the rows from 1985. Create a second data frame with just the rows from 1995. Then, from each of these data frames, get a vector of the number of packs...

...negatively correlated, or uncorrelated? Explain why your answer would be expected.
Change your scatter plot to show the points for each year in a different color. Does the relationship between the two variable change over time?
Do a linear **regression** for these two variables. How much variability does the line explain?
The plot above does not adjust for inflation. You can adjust the price of a pack of cigarettes for inflation by dividing the avgprs variable by the cpi variable. Create an adjusted price for each row, then re-do your scatter plot and linear **regression** using this adjusted price.
Create a data frame with just the rows from 1985. Create a second data frame with just the rows from 1995. Then, from each of these data frames, get a vector of the number of packs...

Depression data to analyze on STATA and present results and interpretation for the **regression** model, frequency tables, plots and others

time period: 1 week ideally
On the dataset:
Can we predict if a customer will default on payments or not?
oversampleling of the smaller class, default column is imbalanced.
Using range of models including:
- Fit a logisitic **regression** model to this data see which solver is best– need to transform to log some of the columns for better results. What is the accuracy score?
o Reduce the dimensionality of the dataset using PCA, any better results?
- Run KNN model
o Same - Reduce the dimensionality of the dataset using PCA, any better results?
- SVM
- XGboost
- And ultimately neural networks – this should be the best
We want highest possible recall score, from classification report
Plot train vs test data accuracy for each model, and ROC curve to see
Optimize hyperparameter...

This is a matlab coding task. I was trying to run a **regression**, most of the codes are done. There are a few variables, momentum, book-to-market, and market cap.. Originally, it runs well with the above variable. I tried to replace one of the variable with another variable (pe ratio) (empirical analysis sheet, row 70), which are also numerical values. However, the **regression** won't work.
Apart from fixing the bug, I have 2 more simple tasks. The first one is to sort the average pe ratio and return according to sector code, the second one is to find the average return and average pe ratio of each year.

For epidemiological research, land use **regression** (LUR) is often employed to estimate air pollution exposures.
Any one who knows how to create LUR model, please bid on this project.
I need you to help me on my research.
More details on chat..
Thank you.

...are in both the Pearson’s correlation and copulas, make another Pearson's correlation and copulas of these clusters separately and compare against the main one. (so, comparing to main Correlation vs Copulas and see how they differ). One cluster with very good dependency, two is medium level dependency and 3 is no dependency.
• Regress the output of one wind farm against another one in a linear **regression** model, then test how well does that fit the data as compared to the copulas model. That will be interesting because then you actually measure whether the copulas does a better job (i.e does this nonlinear relationship that you captured in the copulas model actually improve (or generally is a better model) than the assuming a linear relationship which is what the ...

-This project involves analysis of stories to get trending keywords, to classify the articles to different topics and subtopics, number of words and summarize text.
-To add tags and labels to the articles and check sentiment a...of stories to get trending keywords, to classify the articles to different topics and subtopics, number of words and summarize text.
-To add tags and labels to the articles and check sentiment analysis
-Insert the tags/topics and details to an sql database and update the content details
-To output a list of top articles without similarity
-You must be familiar with content filtering, logistic **regression**, DNN and python
-Additional details will be provided once selected.
-You should have done content analysis before and show how.
-The budget for this project...

Requirements:
1) Manual testing of the important features.
2) Integration testing of the important features using an integration testing framework.
3) Automation testing using Test Cafe frameworks for **regression** testing.
Technical Requirements: Test Cafe with JavaScript/TypeScript
The detailed requirements will be shared once the project is assigned.
Work Duration: 1-2 days.

...Deliverables
A proof-of-concept implementation of bagging, random forests, or boosting both in the case of **regression** and in the case of classification.
Implementing underlying algorithms, such as decision stumps or decision trees; simple proof-of-concept implementations are sufficient.
Final Deliverables
A final program implementing bagging, random forests, or boosting (or all three) with a careful choice of the parameters.
Implementations of the underlying algorithms should be complemented by a careful empirical study of the effect of various parameters; producing optimized programs.
Comparing the performance of different ensemble techniques in the problems of classification and **regression**.
Using bagged and boosted decision trees as probability predictors; evaluating th...

use Deviance as a tool for model checking and testing
-Familiar with Bernoulli, binary, **regression**, where outcomes are 0 or 1.
-generalized linear model theory and Bernoulli **regression** model.

I need help to transpose the years in our excel document.
I want to do a panel data **regression** in stata and I need the years to be in the columns en currently they are placed in a row.
You can find the document attached, you find an example of what needs to be done in the tab 'transportation and storage'.

An excel expert who is able to coach on the use of excel to achieve various statistical analyses such as **regression**, percentages, t-test, correlation, p-values, and descriptive statistics.

...publication of macroeconomic indicators ( & ) - the release date, changes from the previous period and deviationы from expectations, if applicable – with changes of the Fear & Greed Index
Conduct a correlation analysis, propose a **regression** model. Test hypotheses of how publications of macroeconomic indicators (separately and together, published on a monthly and quarterly basis) affects the dynamics of the index during the first 2 weeks after the publication of the indicators.
2. Build a neural network to predict the dynamics of the Fear & Greed Index, depending on the expectations of macroeconomic statistics.
3. Test the model

The projects which I did are about Face Recognition using resnet-50 and multi disease prediction using random forest, logistic **regression** K nearest neighbours, decision tree and tensorflow.

The projects which I did are about Face Recognition using resnet-50 and multi disease prediction using random forest, logistic **regression** K nearest neighbours, decision tree and tensorflow.

I have data set over 10 years showing for 30 districts, the water table level and a number of variables which could have impacted it. Need to use double lasso **regression** in R to identify which variables have more or less or negative effect on the water level

...preferably Java, JUnit, Maven
In this assignment, you are responsible for writing an automated API test for Hotel Booking endpoints.
Assignment Workflow
API Documentation:
Project Requirements
Go through the API documentation above and understand the flow.
Create an API automation suite that can be used as a **regression**.
Target API for the automation
Booking - CreateBooking
Booking - UpdateBooking
Booking- DeleteBooking
Hint: The candidate needs to understand the precondition required to accomplish the above task after going through the API documentation and should be considered as part of the test framework.
Submission
Push your changes to GitHub and give us access or share the code in google drive

...workings needs to be done using Python
- Extracting yield curve factors using Nelson Siegel-Svensson Model
Using US treasury and German bond (monthly data from 1990-2022). I will need you to extract the 4 factors in Nelso Siegel-Svensson model. (Beta 1 - beta 4).
- Forecasting data using: AR, ARIMA and simple Machine Learning Algorithm (Linear **Regression**, Random Forest and SVM)
Make a forecast to those factors. compare AR, ARIMA, Linear **Regression**, Random Forest and SVM. analyse the best forecaster using MAE and RMSE (from the training and test data). we will use the best one to forecast monthly data for the 3 years ahead.
for the corporate bond we will use index (there will be 3 index used) and extract the yield accoring to Nelson Siegel Model and add spread to it. and...

So far in project I have run a standard **regression** with some controls that are included in the data set to see what the relationship between construction costs and house prices is. I now need to employ a difference in difference test to see if this relationship changed across the pandemic and run a granger causality test to cross check my **regression** findings
Once the difference in difference is preformed i need to write 2000 words about the results

I need an expert in Econometrics who’s familiar with Probit and Fixed Effect and running a project in R (only R and not other software). There are three panel data with two different scaling, which requires re-scaling, too. Doing related robustness checks that approve the obtained results plus interpreting the results also required.

Perform
Pearson and Spearman correlation
Chi-squared test (contingency table)
Linear **regression**
Binning, log transformation
Logistic **regression**
Logistic **regression** with co-linearity
etc
Task is
There are some compounds( treat it as a chemical which can kill insects on a plant) .. each compound is made up of 1700+ different things in different ratios.
And target variable is rate of killing, varies from 0-100
We need to find out of 1700+ what is the contribution of each in overall killing..which is making impact on killing.. and I just have 10 compounds
So 10 rows, 1700+ columns

Can you convert Pine Script to Jesse or script? The pine indicator is simple z-score with a bit of twist. It uses sma, **regression** and standard deviation. It has multiple parameters on which I want to be able to run backtesting and parameter optimization. So far I only know of those two programs which can do that relatively easily, just need to get the converted script..
Cheers!

...workings needs to be done using Python
- Extracting yield curve factors using Nelson Siegel-Svensson Model
Using US treasury and German bond (monthly data from 1990-2022). I will need you to extract the 4 factors in Nelso Siegel-Svensson model. (Beta 1 - beta 4).
- Forecasting data using: AR, ARIMA and simple Machine Learning Algorithm (Linear **Regression**, Random Forest and SVM)
Make a forecast to those factors. compare AR, ARIMA, Linear **Regression**, Random Forest and SVM. analyse the best forecaster using MAE and RMSE (from the training and test data). we will use the best one to forecast monthly data for the 3 years ahead.
for the corporate bond we will use index (there will be 3 index used) and extract the yield accoring to Nelson Siegel Model and add spread to it. and...

I have python code that does CNN analysis on dataset, I used CNN and CNN-LSTM models and Random Forest machine learning model. except the RF give 52 accuracy. I want to add Logistic **regression** model to the existing and I want the accuracy above 65, also improve the RF accuracy to be above 70.
I use Python.

i need an indicator added to a strategy :-) this is the strategy this is the indicator

Experience: 6-7 years
Job Description:
1. Experience in ASIC verification, preferably baseband/ controller side
2. E...
4. Experience in HDL(Verilog, VHDL) and HVL(System Verilog, Specman) based functional verification. Experience in code coverage.
5. Experience in Verification methodologies(UVM, OVM and eRM).
language simulation (Verilog-AMS, SystemVerilog).
7. Experience in Mentor, Cadence and Synopsys simulators.
8. Build automated Test bench and **regression** environments from a scratch. Should be able to write a test plan and generate test cases
9. **Regression** management and Verification Sign-off based on Functional Verification and Code Coverage.
10. Gate Level Simulation.
11. Generation of Bus Functional Models, Protocol monitors and checkers.
12. Power simulations using...

...deviation at hand
ii) All data must be visualized logically
iii) Where possible, create/ compile suitable unit-test
* The criterion for choosing the ideal functions for the training function is how they minimize the sum of all ydeviations squared (Least-Square)
** The criterion for mapping the individual test case to the four ideal functions is that the existing maximum
deviation of the calculated **regression** does not exceed the largest deviation between training dataset (A) and
the ideal function (C) chosen for it by more than factor sqrt(2)
In order to give proof of your skills in Python related to this course, you need to adhere to certain criteria when
solving the exercise; these criteria are subsequently described in Uploaded files (details)
Code should be explained in ...

R-Studio Menu and non-linear **Regression**

need help with a newton raphson method for non-linear **regression**

I am looking for a Data Analyst who can help me with an institute project where I need to build a data model using **regression** analysis

We are looking for a Test Lead/Manager to supervise Testing activities in Sin...skills).
• Responsible for creating test plans and strategy
• Reviews and re-evaluates the test strategy to adjust for new information, changing risks, shifting priorities, and schedules
• Oversees testing of software features
• Creating and maintaining of test data and test documentation
• Conducting Test Case Walkthrough with Clients
• Testing End to End Functionality.
• Involving in functional, **regression**, and acceptance tests
• Raising Defects
• Conducting Defect Triage Calls
• Handing Offshore team, Assigning Task, Clarifying Team member questions
• Deploying and managing resources for testing
• Applying the appropriate test measurements a...

this project is to apply :
- extracting yield curve factors using Nelson Siegel-Svensson Model
- Forecasting data using: AR, ARIMA and simple Machine Learning Algorithm (Linear **Regression**, Random Forest and SVM)
- Running Markowitz (mean-variance) Optimization
I need assistance with the above data processing needed for my analysis. Please hit me if you have the skills to run those data and have sufficient financial background related to understanding the context of the analysis.

We are looking for quality assurance engineers on full time contract for 5-6 months with the below skills:
- 4 to 5 years experience in software testing.
- Excellent expertise in API test automation using Rest Assured.
- Hand on in developing **regression** test suites for REST APIs using Rest Assured.
- Good experience in JIRA or ALM.
- Experience in Test management tool (ZEPHYR for JIRA)
- Good at any Object oriented programming knowledge
- Excellent experience on different testing tools.
- Must have ability to write complex SQL queries.
- Excellent experience in manual testing web and mobile applications
Experience in all the above skills is MANDATORY.
Experience: 4-5 years.
Remuneration: 60k-90K per month based on experience.
Location: Bangalore (in-office) as well as Remote (...