ML model development according dataset

This project is for highly trained machine learning expert and futher details are described below, please if you wanted just bid. 1) Perform exploratory data analysis (EDA), and establish hypotheses of predictive insights you expect to glean from the dataset. 2) Perform data preparation for ML informed by the EDA findings. 3) Develop ML model according to hypotheses of predictive insights you gleaned from the dataset. You are required to evaluate at least 3 ML algorithms and assess associated issues i.e. hyperparameters tuning, performance metrics, model complexity (underfitting/overfitting) etc. Finally, provide a recommendation of the best algorithm for your ML model. 4) Documentation: i) Jupyter-Notebook include all coding and technical report i.e. explanations, justifications, reasonings etc. for every finding, strategical decision, action, and choice made. Jupyter-notebook provide a comprehensive documentation capability by using the Markdown ([login to view URL]). ii) Executive Summary Report (maximum 1000 words) to provide an overview of the entire lifecycle of the ML model development, written with target audience in mind such as high-level stakeholders, decision makers, directors etc.