Getting an uber data analysis is not an easy job. Make use of our great guidance and assistance service to have your research work on the right track. We develop synopsis for scholars where the outline of the research work will be stated. All the trending topics and technologies will be used by us to create a project successfully. Get all our research services to achieve your PhD and MS work successfully. We state that, machine learning based Uber trip data analysis offer interpretation into formats, demand forecasting, route optimization and others. Below, we discuss about the development of Uber data analysis concept through the use of machine learning:
A major objective of our goal is to develop a machine learning based framework for demand forecasting for Uber trips in a specific location at a particular period.
Uber Movement: In this, we make use of anonymized information from various locations, data related to city speeds, times and others.
Other Sources: Our work also utilizes Uber trips or ride-sharing based datasets.
Data Cleaning: We preprocess the data by managing missing values, outliers and some abnormalities.
Date-Time Features: Our approach retrieves the data based on time, date such as time of the day, month, day of the week etc.
Spatial Features: Develop features based on distance, categorical regions (such as residential or commercial) or clustering regions if we have coordinates.
Trends over Time: At various time frames, we evaluate the trip demand.
Spatial Analysis: By utilizing heatmaps, more-demand and less-demand regions are visualized by us.
Correlation Analysis: Our project examines the most important feature that contributes to the demand process.
Time Lags: We consider the inclusion of delay features like demand from past days or hours for the time sequence forecasting.
Rolling Averages: To correct the short-term variations and point-out the long-term formats, our work develops features for rolling averages.
Time Series Model: For this, we make use of methods like ARIMA, LSTM, and Prophet by Facebook.
Regression Models: Our approach employs the following techniques if the continuous factors such as number of trips are forecasting.
Decision trees, Linear Regression, Gradient Boosting Machines and Random Forests.
Categorization Models: If the categorical results such as More/Less demand are forecasting, we consider the methods like:
SVM, Logistic Regression and Neural Networks.
Make sure that the training dataset is in a sequential order before the validation and test dataset if we are working with a time series framework.
By using training data, we train our framework.
We consider various metrics such as RMSE, R^2 score or MAE for regression based tasks.
For categorization tasks, we utilize several metrics like accuracy, recall, precision, F1-score and ROC curves.
To optimize the framework parameters, our project uses methods such as random search or grid search.
To offer actual time demand forecasting or to provide interpretation to trip planners or drivers, we implement our framework in applications or dashboards.
Retrain and reconstruct our framework by gathering more data and reviews from users.
We document the research findings and limitations.
Possible future works:
Driver dispatch optimization: To increase the trips, we forecast where drivers must be placed.
Dynamic pricing forecasting: We forecast time periods and regions where the surge pricing may increase.
Route optimization: By considering the previous data, our approach forecasts the fastest route.
External data: We integrate some additional datasets related to weather, city incidents, and holidays that influence the trip demand.
Model Understandability: For developing trust in the framework and obtaining actionable perceptions, it is very important for us to interpret which feature has a huge influence on the forecasting process.
Through the machine learning based Uber data analysis, we optimize the ride-sharing environment, assisting both riders and drivers by forecasting demand, optimizing routes and enhancing overall performance.
Uber Data Analysis Project Using Machine Learning Thesis Topics
Our writers work in different style we assure that your thesis writing will be confidential while readers will be fully engaged. Best thesis topics and ideas related to Uber Data Analysis for your research paper will be offered from our experts. Thus, we ensure a plagiarism free paper with good Grammer quality.
Machine Learning, Quantum Machine Learning, Neural Networks, Support Vector Machine, Logistic Regression
Our paper uses quantum ML (QML) to recognise security datasets. We compare the models like cross models, QML against classical ML (CML), Performance with increasing data size and performance with high iteration numbers and we used ML methods like NN, SVM and LR. Our paper concentrates on evaluate the accuracy of QML and CML method based real world security datasets.
Agriculture, Horticulture, Data Mining
Soil is grave to improving crop yields, the quality of food and its healthiness and nutritive quality. But we may enhance the organic fertilizer and other modern tools and methods. Our paper uses data mining and ML methods like SVM, NB, DT and Linear Discriminant Analyses for predictions and to get a result from agricultural data (CNN). To analyse soil data, soil-borne disease and crop yielding we includes an overview of ML method.
Prediction, Pattern Recognition, Statistical Analysis
Our study sequentially shows the correct statistical validation and then we can done it probably be potential that human destruction can be decreased. Now we have many new and stronger methods can be available. Our paper uses ML methods to study titanic survivals. We used train and test set and comparative study of various ML methods.
data pre-processing, healthcare, exploratory data analysis, heart disease
Our paper discovers the part of Exploratory Data Analysis (EDA) and preprocessing of the heart disease (HD) for the prediction of HD. We used three ML based classifiers namely RF, SVM, DT with missing value imputers, feature scaling methods, data analytics and visualization tools by utilizing four benchmark datasets taken from UCI repository. With the help of our three classifier methods imputation methods were analysed. Random forest with iterative imputer achieves high accuracy.
Crime Analysis, K-Means Clustering, Visualization, NCRB
To define crimes in common law system we used the judicial ruling. The most general crimes are governed by laws and orders. The aim of our paper is to enterprise the people with new site to tell about the crime details and that can be avoiding target of any crime. The user can clearly understand the common crimes and analyse how each crime can happens in various part of the state in extensive analysis of crime data.
Big data, data analytics, healthcare, disease prediction
We used big data analytic to help healthcare evolve. To identify the problem, we have to keep possible health issues and give the solution before it degrades. ML and big data methods have influence on healthcare industries. Our paper concentrates on ML and big data analytics to identify particular diseases at starting stage or by predict best health services.
Udemy Course, Kaggle, Random Forest
Our paper aims to predict the salary of the trainers in Udemy course and to discover the datasets. First we have to gather the dataset from kaggle then we have ro preprocess the datasets and then the exploratory data analysis is executed and predicted and then the execution of ML random forest method can be executed. Our study displays n-estimator of ML random forest techniques gives the better prediction.
BP neural network, Wordle
We have to preprocess the data by choosing to construct a BP neural network, by digitally alter the words to decide the input and output layers. We used ML to modify the reasonable parameters and at last the data has been processed and predicted after the error analysis. To classify the word we use optimization method such as SSE; “elbow” method – K-value determination; CH coefficient, etc. ML method can also be used to analyse cluster model and exploratory data analysis can decrease the dimensionality and visualization.
behavioural artifacts, web user data analysis, attribute ratio rule, spatio temporal
We have to analyse the web user data to for behavioural artifact detection using ML methods. We can smoothen and remove noise by gathering and process the web user data. Then our data can be trained and chosen for detection of malware activities by utilizing attribute rule-based auto encoder training. Chosen data can be classified by spatio temporal q-learning method.
Learning systems, Solar data, Space Weather.
Our paper explores automated analysis of association among various solar events and activities. We also used many association methods on computer tool that allow advanced learning. Our goal is to merge all data catalogue in one dynamic weather database and can easily utilize solar activities and features. The computer tool offer numerical representation and identifies pattern of association and that can be used for input to ML.
Before sit down to research proposal writing, we need to decide exact journals. For e.g. SCI, SCI-E, ISI, SCOPUS.
As a doctoral student, subject selection is a big problem. Phdservices.org has the team of world class experts who experience in assisting all subjects. When you decide to work in networking, we assign our experts in your specific area for assistance.
We helping you with right and perfect topic selection, which sound interesting to the other fellows of your committee. For e.g. if your interest in networking, the research topic is VANET / MANET / any other
To ensure the novelty of research, we find research gaps in 50+ latest benchmark papers (IEEE, Springer, Elsevier, MDPI, Hindawi, etc.)
After literature survey, we get the main issue/problem that your research topic will aim to resolve and elegant writing support to identify relevance of the issue.
Based on the research gaps finding and importance of your research, we conclude the appropriate and specific problem statement.
Writing a good research proposal has need of lot of time. We only span a few to cover all major aspects (reference papers collection, deficiency finding, drawing system architecture, highlights novelty)
We prepare a clear project implementation plan that narrates your proposal in step-by step and it contains Software and OS specification. We recommend you very suitable tools/software that fit for your concept.
We get the approval for implementation tool, software, programing language and finally implementation plan to start development process.
Our source code is original since we write the code after pseudocodes, algorithm writing and mathematical equation derivations.
We implement our novel idea in step-by-step process that given in implementation plan. We can help scholars in implementation.
We perform the comparison between proposed and existing schemes in both quantitative and qualitative manner since it is most crucial part of any journal paper.
We evaluate and analyze the project results by plotting graphs, numerical results computation, and broader discussion of quantitative results in table.
For every project order, we deliver the following: reference papers, source codes screenshots, project video, installation and running procedures.
We intend to write a paper in customized layout. If you are interesting in any specific journal, we ready to support you. Otherwise we prepare in IEEE transaction level.
Before paper writing, we collect reliable resources such as 50+ journal papers, magazines, news, encyclopedia (books), benchmark datasets, and online resources.
We create an outline of a paper at first and then writing under each heading and sub-headings. It consists of novel idea and resources
We must proofread and formatting a paper to fix typesetting errors, and avoiding misspelled words, misplaced punctuation marks, and so on
We check the communication of a paper by rewriting with native English writers who accomplish their English literature in University of Oxford.
We examine the paper quality by top-experts who can easily fix the issues in journal paper writing and also confirm the level of journal paper (SCI, Scopus or Normal).
We at phdservices.org is 100% guarantee for original journal paper writing. We never use previously published works.
We play crucial role in this step since this is very important for scholar’s future. Our experts will help you in choosing high Impact Factor (SJR) journals for publishing.
We organize your paper for journal submission, which covers the preparation of Authors Biography, Cover Letter, Highlights of Novelty, and Suggested Reviewers.
We upload paper with submit all prerequisites that are required in journal. We completely remove frustration in paper publishing.
We track your paper status and answering the questions raise before review process and also we giving you frequent updates for your paper received from journal.
When we receive decision for revising paper, we get ready to prepare the point-point response to address all reviewers query and resubmit it to catch final acceptance.
We receive final mail for acceptance confirmation letter and editors send e-proofing and licensing to ensure the originality.
Paper published in online and we inform you with paper title, authors information, journal name volume, issue number, page number, and DOI link
We pay special attention for your thesis writing and our 100+ thesis writers are proficient and clear in writing thesis for all university formats.
We collect primary and adequate resources for writing well-structured thesis using published research articles, 150+ reputed reference papers, writing plan, and so on.
We write thesis in chapter-by-chapter without any empirical mistakes and we completely provide plagiarism-free thesis.
Skimming involve reading the thesis and looking abstract, conclusions, sections, & sub-sections, paragraphs, sentences & words and writing thesis chorological order of papers.
This step is tricky when write thesis by amateurs. Proofreading and formatting is made by our world class thesis writers who avoid verbose, and brainstorming for significant writing.
We organize thesis chapters by completing the following: elaborate chapter, structuring chapters, flow of writing, citations correction, etc.
We attention to details of importance of thesis contribution, well-illustrated literature review, sharp and broad results and discussion and relevant applications study.
Novelty is essential for a PhD degree. Our experts are bringing quality of being novel ideas in the particular research area. It can be only determined by after thorough literature search (state-of-the-art works published in IEEE, Springer, Elsevier, ACM, ScienceDirect, Inderscience, and so on). SCI and SCOPUS journals reviewers and editors will always demand “Novelty” for each publishing work. Our experts have in-depth knowledge in all major and sub-research fields to introduce New Methods and Ideas. MAKING NOVEL IDEAS IS THE ONLY WAY OF WINNING PHD.
To improve the quality and originality of works, we are strictly avoiding plagiarism since plagiarism is not allowed and acceptable for any type journals (SCI, SCI-E, or Scopus) in editorial and reviewer point of view. We have software named as “Anti-Plagiarism Software” that examines the similarity score for documents with good accuracy. We consist of various plagiarism tools like Viper, Turnitin, Students and scholars can get your work in Zero Tolerance to Plagiarism. DONT WORRY ABOUT PHD, WE WILL TAKE CARE OF EVERYTHING.
We intended to keep your personal and technical information in secret and it is a basic worry for all scholars.
CONFIDENTIALITY AND PRIVACY OF INFORMATION HELD IS OF VITAL IMPORTANCE AT PHDSERVICES.ORG. WE HONEST FOR ALL CUSTOMERS.
Most of the PhD consultancy services will end their services in Paper Writing, but our PhDservices.org is different from others by giving guarantee for both paper writing and publication in reputed journals. With our 18+ year of experience in delivering PhD services, we meet all requirements of journals (reviewers, editors, and editor-in-chief) for rapid publications. From the beginning of paper writing, we lay our smart works. PUBLICATION IS A ROOT FOR PHD DEGREE. WE LIKE A FRUIT FOR GIVING SWEET FEELING FOR ALL SCHOLARS.
After completion of your work, it does not available in our library i.e. we erased after completion of your PhD work so we avoid of giving duplicate contents for scholars. This step makes our experts to bringing new ideas, applications, methodologies and algorithms. Our work is more standard, quality and universal. Everything we make it as a new for all scholars. INNOVATION IS THE ABILITY TO SEE THE ORIGINALITY. EXPLORATION IS OUR ENGINE THAT DRIVES INNOVATION SO LET’S ALL GO EXPLORING.
I ordered a research proposal in the research area of Wireless Communications and it was as very good as I can catch it.
I had wishes to complete implementation using latest software/tools and I had no idea of where to order it. My friend suggested this place and it delivers what I expect.
It really good platform to get all PhD services and I have used it many times because of reasonable price, best customer services, and high quality.
My colleague recommended this service to me and I’m delighted their services. They guide me a lot and given worthy contents for my research paper.
I’m never disappointed at any kind of service. Till I’m work with professional writers and getting lot of opportunities.
Once I am entered this organization I was just felt relax because lots of my colleagues and family relations were suggested to use this service and I received best thesis writing.
I recommend phdservices.org. They have professional writers for all type of writing (proposal, paper, thesis, assignment) support at affordable price.
You guys did a great job saved more money and time. I will keep working with you and I recommend to others also.
These experts are fast, knowledgeable, and dedicated to work under a short deadline. I had get good conference paper in short span.
Guys! You are the great and real experts for paper writing since it exactly matches with my demand. I will approach again.
I am fully satisfied with thesis writing. Thank you for your faultless service and soon I come back again.
Trusted customer service that you offer for me. I don’t have any cons to say.
I was at the edge of my doctorate graduation since my thesis is totally unconnected chapters. You people did a magic and I get my complete thesis!!!
- Abdul Mohammed
Good family environment with collaboration, and lot of hardworking team who actually share their knowledge by offering PhD Services.
I enjoyed huge when working with PhD services. I was asked several questions about my system development and I had wondered of smooth, dedication and caring.
I had not provided any specific requirements for my proposal work, but you guys are very awesome because I’m received proper proposal. Thank you!
I was read my entire research proposal and I liked concept suits for my research issues. Thank you so much for your efforts.
- Ghulam Nabi
I am extremely happy with your project development support and source codes are easily understanding and executed.
Hi!!! You guys supported me a lot. Thank you and I am 100% satisfied with publication service.
I had found this as a wonderful platform for scholars so I highly recommend this service to all. I ordered thesis proposal and they covered everything. Thank you so much!!!