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    814 multivariate jobs found, pricing in GBP

    ...- SPSS proficiency - Versatility in various data analysis tasks Those willing to bid on this project should; - Highlight their SPSS proficiency and mastery in their responses. - Include their direct and equivalent experience in data analysis using SPSS software. - Linear models: Introduction to linear models Fitting linear models Multivariate linear models Assessing confounders and interactions Fitting and interpreting linear Models with several predictors. - Logistic regression: Interpreting logistic regression models. Model fit, selection and testing logistic regression assumption. Re...

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    I'm in need of an experienced pattern maker to help with my clothing line. The aim is to create unique and stylish patterns for tops, bottoms and outerwear. The clothing patterns required should cater to a broad size range, encompassing small, medium and large sizes. It would be fantastic if you have extensive experience creating diverse pattern sizes. Multivariate detailing and intricate design knowledge is highly appreciated. Let's create fashion that fits and flatters all body types.

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    Analyze the dataset in respect to the provided research aims

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    I'm in need of a professional who can assist with regression analysis on a survey data. Specifically, the job involves analysing a dataset with more than two variables. Key responsibilities and tasks involved: - Conducting a multivariate regression analysis on the provided survey data. - Interpreting the results and creating an easy-to-understand report. Ideal Skills: - Strong proficiency in statistics and experienc in regression analysis. - Deep knowledge of statistical software such as R, SPSS or similar. - Prior experience with survey data analysis. - Excellent report writing skills, with the ability to simplify complex data. - Accuracy and attention to detail. Candidates who can provide sample projects or case studies of similar work performed will be given priority. ...

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    I am looking to enhance the promotion of my parking garage business. It aims to draw local residents, tourists, business professionals, cruise, and military parking clients. My establishment offers both daily and monthly parking services to accommodate multivariate customer needs. Currently, I rely on social media marketing, print advertising, and word-of-mouth referrals to spread awareness about my business, but I'm open to innovative ideas. Ideal freelancers for this project will have a rich background in marketing, a creative mind, and specific experience in promoting similar businesses. Your contribution will help maximize our reach and customer conversion.

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    I'm seeking a proficient statistics professional, who is skilled in performing Multivariate Regression Analysis. A Quick Overview I have gathered a decent amount of scientific experiment data, and my primary need is to analyze this data through multivariate regression, identify key relationships and trends, and interpret the results accurately. I need a statistical expert for the analysis of the data for a thesis titled 'Assessing key determinants of housing prices: A case of Pune' with the objective to 1. To define factors influencing housing prices in the Indian context 2. To measure the impact of each factor on housing prices 3. To identify variations in housing prices corresponding to property attributes Data will be provided you are expected to clea...

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    I'm seeking a highly skilled Python developer with a background in finance and exceptional skills in data analysis. This project involves creating a financial forecasting model using Python. Key tasks: - To work with historical sales data, which is multi-variable in nature. - The main task is financial forecasting based on the data provided. Required skills: - A solid understanding of Python is crucial. - Experience in financial analysis, particularly financial forecasting. - Proficiency in working with multi-variable data. - A keen eye for detail and accuracy. If you have proven experience in Python and financial data analysis, I welcome you to bid on this project. Your prior experience in forecasting using multi-variable data will be a value addition.

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    ...of; • Data analysis • Reading understanding and utilizing varying types of data • Python programming The expertise isn't limited to these but an added grasp on web scraping and machine learning would be highly beneficial. The type of data to be analyzed is currently undisclosed. If you fit the description, waste no time in bidding. I look forward to your proposals. • Compute the Multivariate Mean Vector: Calculate the mean for each attribute in the dataset. • Compute the Sample Covariance Matrix (Inner Product): Use the inner product between the columns of the centered data matrix(Numerical Attributes only). • Compute the Sample Covariance Matrix (Outer Product): Use the outer product between the centered data points(Numerical Att...

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    ...seek someone able to adapt quickly, bringing fresh ideas to the table. Own and develop campaign tagging & tracking to ensure all marketing can be accurately measured through both online & offline conversion Work with relevant teams to drive volume growth and efficiencies by proactively identifying trends and insights to help drive conversion improvement Responsibility for implementing A/B, multivariate & personalisation testing, and reporting of results, including statistical significance (where applicable) Provide ad-hoc analysis and deeper dives into areas of opportunity, including performance marketing & new digital change initiatives Devise, develop and maintain reports, dashboards, presentations & data visualisation (including automation where possible),...

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    Project Description: I am seeking a skilled freelancer to implement a multivariate timeseries transformer model for predicting runoff based on rainfall data. The task involves leveraging the provided dataset, which comprises three essential columns: rainfall, runoff, and datetime. As the project owner, I will supply the necessary dataset and GitHub repository link containing the model architecture and implementation guidelines. Key Responsibilities: Implement a multivariate timeseries transformer model using the provided dataset. Utilize the rainfall and datetime information to forecast runoff accurately. Ensure adherence to best practices in machine learning model development and deployment. Collaborate closely with me to address any project-specific requirements or modif...

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    I'm looking to optimize my website's search engine results to ultimately drive more traffic and generate more leads. Although I don't have specific goals laid out just yet, it's crucial that the freelancer understands how to both attract and maintain attention to my site. In the absence of specific instruction...audience or customer demographic hasn't been established yet, so the ideal freelancer should be flexible in their strategy and capable of targeting various groups such as young adults, parents, and business professionals, as the project evolves. Ideal skills and experience include: - Proven SEO experience - Knowledge of ranking factors and search engine algorithms - Experience with A/B and multivariate experiments - Strong analytical skills - Up-t...

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    I have data for 178 head and neck cancer patients. I have done univariate and multivariate analysis for prognostic factors for locoregional control (LRC) and Overall survival (OS). Im calculating median LRC, 2 years LRC and 5 years LRC, median OS) 2 years OS and 5 years OS. I have run Kaplan-Meier curve myself and can see the median LRC and OS, but i dont where to look for 2 years and 5 years LRC and OS from survival table or KM curve. I need to know where to look for these.

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    I am looking for a statistics expert to assist me with my PhD research. The project involves conducting multivariate analysis on my data. I prefer to use SPSS for analyzing the data. The timeline for the project is not urgent, and I would like to complete it within 1-3 weeks. You must be fluent in English so that there are no communication barriers. Ability to use R in addition to SPSS would be useful as I believe R generates better visualisation graphics than SPSS Ideal skills and experience: - Strong background in statistics and experience with multivariate analysis - Proficiency in using SPSS for data analysis - Familiarity with PhD research requirements and methodologies Please respond only if you have specifically managed data on diabetes-risk and or diabetes self-mana...

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    ...challenge is to create a simple insurance price forecasting tool based on historical pricing data. Specifically: 1. We have an excel sheet with 14,073 rows and 7 columns. 2. Columns are; insurance price, Vehicle Make, Vehicle Model, Vehicle Year, Driver Gender, Driver Age, Driver Location (name of an Australian State). 3. The rows are insurance prices. We want to create a forecasting model using multivariate regression, or another approach, to be able to forecast what the dependant variable (insurance price) might be based on the various independent variables, such as vehicle make, model, year and various driver characteristics. The reason why we need help is that the data has a large number of categorical variables. There are 43 different types of vehicle makes and 434 diff...

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    Part 1 - Exploratory Data Analysis In this first part, you will conduct an exploratory data analysis on a dataset of your choice. Use Python data science and data visualization libraries to explore the dataset’s variables and understand the data’s structure, oddities, patterns, and relationships. The analysis in this part should be structured, going from simple univariate relationships to multivariate relationships, but it does not need to be clean or perfect. There is no single answer that needs to come out of a given dataset. This part of the project is your opportunity to ask questions about the data and make your discoveries. It’s essential to keep in mind that sometimes exploration can lead to dead ends and that it can take multiple steps to dig down to what ...

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    In this project, I am seeking expert assistance to efficiently and accurately replicate the data analysis process of a specific scientific paper (appendix). The task predominantly focuses on the facet of data analysis, particularly multivariate regression. I need especially help with acquiering the data from Eikon by Thomson Reuters, bringing it into a proper data format to analyse it in python. We are using different regression strategies (linear, multivariable, panel, instrument variable) and we will be working with Asset pricing models (e.g. Fama French). Skills and Experience: • Proficiency in statistical analysis and econometric modeling, including experience with software such as Python • Understanding of financial markets, corporate bonds, and climate risk pricing ...

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    ...robustness of its conclusions. Methodological Extension: Alternatively, you can opt to add to an existing paper by applying a different time series method. Main Topics Maximum Likelihood Estimation Autocorrelation Univariate Time-Series Models Forecasting High-Frequency Data and Financial Time-Series Models Spurious Regressions and Filtering Techniques Unit Roots and Cointegration Multivariate Time-Series Models Binary Choice Models only need the analysis Requirements: rmd file Requirements: - The project requires conducting predictive analysis on a specific dataset provided by the client. - The dataset is already available and ready for analysis. - The analysis needs to be completed within 1 day. If you have the necessary skills and experience in predictiv...

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    I have a project that requires a deep learning model (Graphical Neural Ne...requires a deep learning model (Graphical Neural Networks) for classification, using numerical data. I already have a dataset available for the model. This will involve identifying patterns in the data and then predicting outcomes, the end goal being to develop a model that can accurately classify data and provide reliable predictions. there must be usage of GNN(graphical neural networks) , show multivariate graph,show graphical networks, and apply stem GNN and (if req. other model too) get the best accuracy possible. this project is for anomaly detection using ecg data , prediction could be - anomaly is there or not. If you think you have the necessary skills and knowledge required for this project, ple...

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    I need a help for writing an article about Leveraging Business Data Analytics for Robust Category Management: A Pathway to Drive Category Growth. An outline: Introduction Business Data Analytics (BDA) and Category Management are two pivotal facets in modern retail and business environments. BDA employs statistical analysis, predictive modeling, and multivariate testing among others to derive meaningful insights from data. On the other hand, Category Management is a retailing and purchasing concept where a range of products is managed as a strategic business unit to meet customer needs and enhance profitability. The fusion of BDA and Category Management paves the way for refined decision-making, optimized operations, and ultimately, accelerated category growth. Section 1: Understa...

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    I am in need of a skilled Matlab programmer who can assist me with my project. The ideal candidate should be proficient in importing spectral data and have experience in writing scripts to model the data using multivariate analyses. Requirements: - Proficiency in Matlab programming language - Ability to import and manipulate spectral data - Experience in writing scripts for data modeling - Familiarity with multivariate analyses - Capable of both editing and evaluating existing scripts, as well as creating scripts from scratch - Experience in Generating Apps and GUI to facilitate program execution also a plus Specifics: - The script will be modeling spectral data ranging from 250 to 1000 nm - The primary analysis required is Principal Component Analysis (PCA), Partial Leas...

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    ... and checkout process. Ideal Skills and Experience: - Proven track record in CRO, with a focus on increasing sales and improving user experience. - Expertise in analyzing website data and metrics to identify conversion bottlenecks and areas for improvement. - Strong understanding of user behavior and psychology to optimize website elements and user flows. - Proficiency in A/B testing and multivariate testing to measure the impact of different optimization strategies. - Experience with optimizing homepage design, product pages, and checkout process, including reducing friction and improving usability. - Familiarity with popular CRO tools and platforms to implement and track optimization efforts. If you are a results-driven CRO specialist who can help us enhance our website...

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    ...expertise, but any exposure is a great perspective. ā— Experience in using version control systems like Git ā— Experience with state management libraries (e.g.. MobX) and asynchronous programming. ā— Solid experience in documenting software solutions using diagrams and flowcharts. ā— Experience in release management, online digital analytics, conversion optimization test execution like a/b testing and multivariate testing, search engine optimization/marketing, social media marketing management, strategies and execution is an added advantage. ā— Strong multi-tasking, organization and time management skills to manage multiple projects, deadlines and priorities within budget requirements ā— Exceptional collaborative and interpersonal skills; dynamic flexible team player with the ability t...

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    Project Title: Transformers for time series forecasting Overview: I am seeking a skilled freelancer to develop a time series forecasting model using multivariate forecasting techniques. The goal of the project is to accurately predict future outcomes based on Electric vehicle data using the Python programming language. Requirements: - Expertise in multivariate forecasting is essential for this project, as the model will need to take into account multiple variables in order to generate accurate predictions. - Strong knowledge of time series analysis and statistical modeling is required to ensure the accuracy and reliability of the forecasting model. - Proficiency in Python is a must, as the preferred programming language for this project. Experience with libraries such as Pa...

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    I am looking for an experienced data scientist to help me with multivariate time series forecasting. My data is sampled monthly and I need to predict results for more than 6 steps ahead. I am agnostic on the forecasting method, as I have no preference. The successful candidate should have a proven track record in working with time series forecasting. I look forward to reviewing proposals from skilled data scientists!

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    ...be comfortable working in a fast-paced, dynamic environment and be able to communicate effectively with our other teams. The successful candidate should also be familiar with the latest technologies and trends in backend development. A competitive salary will be offered to the right candidate. What You’ll Do - Develop, test and maintain backend products and services - Run high-impact A/B and multivariate testing experiments at scale, analyzing results, and deploying positive changes to reach business goals - Problem solving: think of and then implement solutions to technical problems presented by the product team - Design and implement backend server architectures - Monitor and optimize performance of existing systems - Work closely with engineering and product teams to en...

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    ...Proven working experience in digital marketing. • Demonstrable experience leading and managing SEO/SEM, marketing database, email, social media, and/or display advertising campaigns. • Highly creative with experience in identifying target audiences and devising digital campaigns that engage, inform, and motivate. • Experience in optimizing landing pages and user funnels. • Experience with A/B and multivariate experiments. • Solid knowledge of website analytics tools (e.g., Google Analytics, Net Insight, Omniture, Web Trends). • Working knowledge of ad serving tools (e.g., DART, Atlas). • Experience in setting up and optimizing Google Ad Words campaigns. • Working knowledge of HTML, CSS, and JavaScript development and constraints. • Str...

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    Non-parametric Multivariate analysis, non-parametric regression analysis, index creation, SAS. Experience in organizational research and observational data

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    ...field -Proven working experience in digital marketing -Demonstrable experience leading and managing SEO/SEM, marketing database, email, social media and/or display advertising campaigns -Highly creative with experience in identifying target audiences and devising digital campaigns that engage, inform and motivate -Experience in optimizing landing pages and user funnels -Experience with A/B and multivariate experiments -Solid knowledge of website analytics tools (e.g., Google Analytics, NetInsight, Omniture, WebTrends) -Working knowledge of ad serving tools (e.g., DART, Atlas) -Experience in setting up and optimizing Google Adwords campaigns -Working knowledge of HTML, CSS, and JavaScript development and constraints -Strong analytical skills and data-driven thinking -Up-to-date wi...

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    I am looking for an experienced data analyst to help me with multivariate time series forecasting. The data to be analyzed is from the past less than 1 year. I am not sure which forecasting technique to use and would appreciate recommendations. However, I prefer the use of R for this project. Ideal skills for this project include: - Proficiency in R programming language - Expertise in time series forecasting techniques such as ARIMA and LSTM Neural Networks - Experience in analyzing and interpreting multivariate time series data.

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    ...to achieve the business objectives 4. Create content and manage the content creation process. 5. End-to-end management of existing paid campaigns, tracking monitoring of relevant KPIs, and metrics, analysis of results, and calibration of campaigns to maximize ROI 6. Provide insights, recommendations, and action plans based on the analysis of the performance report. Implement relevant AB and multivariate testing on the campaigns, Landing Pages, and other relevant channels or platforms as necessary to improve campaign performances 7. Keep current on emerging digital tools and platforms, digital marketing trends, and new technologies, and share insights with the rest of the team. 8. Collaborate with other teams to produce creative and engaging campaigns Skills and Qualifications: 1...

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    Patients with abdominal pain after bariatric surgery. I do have a total of 1297 patients of those 90 patients were found to have abdominal pain. I have the main data collected on an excel spreadsheet for the main population. I would need demographic...have a total of 1297 patients of those 90 patients were found to have abdominal pain. I have the main data collected on an excel spreadsheet for the main population. I would need demographics of those. I have in another spreadsheet the actual 90 patients who developed pain. I would need demographics and any correlation of those factors with the development of abdominal pain. Univariate / multivariate analysis. The aim is defining not only a management strategy but also trying to predict the increased risk for abdominal pain deve...

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    We are seeking an experienced Machine Learning Engineer. The project invol...variables, including temperature and humidity, which are collected from a climate-controlled environment. The predictions will be based on 28 independent variables, with the aim of forecasting the dependent variables at various time horizons, ranging from 1 to 8 hours. The ideal candidate will leverage their expertise in Long Short-Term Memory (LSTM) networks, or similar technologies, to handle this multivariate time-series forecasting task. The data set consists of over 500,000 observations gathered over a span of more than a year. The input to NN has to be editable enabling the change in the last observations before prediction. The project has to contain documentation on evaluation metrics and their inter...

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    Need assistance with building a multivariate time series ML model to predict ASX200 closing price. Currently have multiple potential key "importance features" that i'd like to test out. Person would ideally have proven experience in using LTSM networks and/or Auto-regressive Distributed Lags Model. Keen to work with someone who is transparent on all the steps taken to manipulate the data, train, test, etc.

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    In R Studio please do all three problems. I have provided all the files attachment links needed to complete the project

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    i can share my requirements basically KLT point-tracking algorithm. Stereo correspondences are found using an optimized block-matching algorithm using the normalized cross-correlation metric. These disparity values are used to triangulate two-point clouds at successive steps in frames, after which a weighted least-squares pose estimation algorithm is run ...my requirements basically KLT point-tracking algorithm. Stereo correspondences are found using an optimized block-matching algorithm using the normalized cross-correlation metric. These disparity values are used to triangulate two-point clouds at successive steps in frames, after which a weighted least-squares pose estimation algorithm is run to estimate the pose change between timesteps. A multivariate gaussian anomaly detection...

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    I’m looking to establish a mathematical model which helps us optimise our small business margins on social media ad spends. I think this may need a multivariate analysis approach because there are a number of variables to consider, some within our control, others outside. They include Cost of advertising per unit Selling price of product Purchase cost of product No of visitors to our site following ad campaign Conversion rate of visitor to buyer Our product proposition relative to the market Outside external factors - eg competitor propositions, seasonality, Black Friday In summary we seek to devise a model which helps us maximise gross margin less ad spend. Many thanks for reading this and I hope you can help

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    design of a portable visual odometry system that utilizes a feature-based stereo visual odometry, with IMU assistance. The focus is on d...successive frames using a KLT point-tracking algorithm. Stereo correspondences are found using an optimized block-matching algorithm using the normalized cross-correlation metric. These disparity values are used to triangulate two-point clouds at successive steps in frames, after which a weighted least-squares pose estimation algorithm is run to estimate the pose change between timesteps. A multivariate gaussian anomaly detection algorithm is used to reject outliers due to poor matching or moving objects. Finally, a Kalman filter is exploited to enforce a constant-acceleration dynamic model on the cameras, and fuse IMU data for better attitude e...

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    I am looking for a qualified tutor to help my student with single and multivariate calculus, linear algebra, statistics and discrete math. The goal is to answer basic questions in those courses. More in chat.

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    I am trying to predict for 2023 applications using bill rate and orders from 2019-2022

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    Engineering for Feature. On the basis of data on typical electricity consumption, select a subset of the response variables for multivariate Hidden Markov model training. You must run a Principal Component Analysis (PCA), which is a better option than utilising a correlation matrix, to choose the subset of variables that are most appropriate for training your models. Based on your PCA results, give a proper justification for the final response variables you chose. The following page goes into greater depth about this technique. Keep in mind that before performing PCA, the raw data must be scaled using normalisation.

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    ...Knowledge of ranking factors and search engine algorithms Demonstrable experience leading and managing SEO/SEM, marketing database, email, social media, and/or display advertising campaigns Highly creative with experience in identifying target audiences and devising digital campaigns that engage, inform and motivate Experience in optimizing landing pages and user funnels Experience with A/B and multivariate experiments Solid knowledge of website analytics tools (e.g., Google Analytics, NetInsight, Omniture, WebTrends) Working knowledge of ad serving tools (e.g., DART, Atlas) Experience in setting up and optimizing Google Adwords campaigns Working knowledge of HTML, CSS, and JavaScript development and constraints Strong analytical skills and data-driven thinking Up-to-date with th...

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    We are looking for an SEO/SEM expert to manage all search engine optimization and marketing activities. You will be responsib...experience Proven SEM experience managing PPC campaigns across Google, Yahoo and Bing. Solid understanding of performance marketing, conversion, and online customer acquisition In-depth experience with website analytics tools (e.g, Google Analytics, NetInsight, Omniture, WebTrends) Experience with bid management tools (e.g., Click Equations, Marin, Kenshoo, Search Ignite) Experience with A/B and multivariate experiments Working knowledge of HTML, CSS, and JavaScript development and constraints Knowledge of ranking factors and search engine algorithms Up-to-date with the latest trends and best practices in SEO and SEM BS/MS degree in a quantitative, test-dr...

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    We are looking to find more clients since we h...end custom analytics, programming and consulting for survey research. Offering quick turnaround with highly experienced programmers, clients can expect the highest level of service without the need for hirinng an in house DP department as well as on call consultants for any market research need. We offer survey analysis through statistical processing (cross tabulations, project consulting, multivariate modelling for segmentation etc.) We have conducted analysis and consulting for a wide range of private corporations including many fortune 500 companies. There is no dedicated sales department in our operation and we are intersted in paying to have help aquiring new cleints. Competative commissions are available for help aquiring new...

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    design of a portable visual odometry system that utilizes a feature-based stereo visual odometry, with IMU assistance. The focus is on d...successive frames using a KLT point-tracking algorithm. Stereo correspondences are found using an optimized block-matching algorithm using the normalized cross-correlation metric. These disparity values are used to triangulate two-point clouds at successive steps in frames, after which a weighted least-squares pose estimation algorithm is run to estimate the pose change between timesteps. A multivariate gaussian anomaly detection algorithm is used to reject outliers due to poor matching or moving objects. Finally, a Kalman filter is exploited to enforce a constant-acceleration dynamic model on the cameras, and fuse IMU data for better attitude e...

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    ...algorithms applicable to the dataset. This includes plotting, training, testing, tuning and optimizing each model to make 10 types of predictions (see attached file for more details): • Regression Models ā—‹ Linear Regression ā—‹ Ridge Regression ā—‹ Polynomial Regression ā—‹ Multiple Linear Regression ā—‹ Lasso Regression (Least Absolute Shrinkage and Selection Operation) aka Penal Regression ā—‹ Multivariate Adaptive Regression Splines (MARS) • Clustering Models ā—‹ K-Means ā—‹ Hierarchical (Agglomerative / Divisive) ā—‹ Affinity Propagation ā—‹ BIRCH ā—‹ DBSCAN ā—‹ K-Means ā—‹ Mini-Batch K-Means ā—‹ Mean Shift ā—‹ OPTICS ā—‹ Spectral Clustering ā—‹ Mixture of Gaussians • Artificial Neural Networks (ANNs) ā—‹ DNN - Dense Neural Network ā—‹ Perceptron ā—‹ Radial Basis Function Neu...

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    Looking for a consultant to help us understand methods for determining the uncertainty associated with models we use in the semiconductor industry. Our models are multivariate and nonlinear, but they are trained on input data collected from semiconductor fabs, and for each of thousands of samples (with different characteristics) measured, there are multiple repeat measurements done across some spatial domain such that the mean values for each characteristic are entered into the model training, but in some cases the 95% CI associated with determination of each mean value is also known. We are trying to understand generally how to determine the MODEL PREDICTION 95% CI for the two scenarios of a) only mean values input to the model and b) both mean and 95% CI for measured input data ...

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    I have attached the project from a pdf. NEED THIS IN R Programming

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    Multivariate methods - R Programming advanced in html - urgent work

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