Research and Prototyping : Ensemble Learning

Hi I am a very experienced statistician, data scientist and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, PYTHON, WEKA, TABLEAU, POWER BI, and EXCEL tools like machine learning, deep learning, AI, NLP, hypothesis testing, forecasting, T-test, ANOVA etc. Looking forward to discussion, Best Regards, Suyash

1. I am an expert in writing research on Ensemble Learning with unique content without plagiarism. I read your project description and I am sure that I can handle your project. 2. Also an expert in Academic writing, research reports, essays and advance essays, dissertations. 3. I will ensure that your project will be delivered on time with high standard. 4. Expert in all referencing styles (APA/ Harvard / IEEE /MLA/etc.). 5. 100 % Assurance on zero percent plagiarism. 6. TURNITIN / COPYSCAPE plagiarism report will be provided along with completed work 7. Assistance will be provided with the number of clarifications until client satisfaction 8. I will provide assistance even after the payment. And will maintain data (content)security.

Hi, Greetings. I am interested to work in this project based on its description. However, I would like to understand more on the requirements on what aspect of research would you be interested in ensemble learning. Based on the initial requirement, I have proposed a ballpark quote of INR 20,000. For a detailed split up on milestones, its plan and associated budget breakup, I might require few more details on the project. Do you have document illustrating the project requirements? If not, we may discuss on the requirements over a call. Please revert with your inputs. Thanks Ishwarya

Do a comprehensive literature review on Topic Ensemble Learning. Find a research gap in existing Topic Ensemble Learning. Develope a solution to the gap. Validate the solution with a suitable dataset.