End To End Guide For Machine Learning Project

We find many informative articles online providing an in-depth coverage of how we need to implement parts of a machine learning/data science project but at times, we just need high level steps offering clear guidance.When I was new to machine learning and data science, I used to seek articles that clearly outlined the steps stating what I need to do to get my project done.This article aims to provide an end-to-end guide for getting a successful machine learning project implemented.With That In Mind, Let’s StartIn a nutshell, a machine learning project has three main parts: Data Understanding, Data Gathering & Cleaning, And Finally Model Implementation And Tuning..Usually, Data Understanding, Gathering And Cleaning Takes 60–70% Of The Time..And For That, We Need A Domain Expert.ScenarioLet’s imagine you are attempting to work on a machine learning project..This article will provide you with the step to step guide on the process that you can follow to implement a successful project.In the beginning, there are multiple questions arising in our brainData Science Is Trial And Error, It’s Research And Recursive, It’s Practical And Theoretical, It Requires Domain Knowledge, It Boosts Your Strategic Skills, You Learn About Statistics And Master Programming Skills..But Most Importantly, It Teaches You To Remain Patient As You Are Always Close To Finding A Better Answer.StepsTwo Pre-requisite Steps:1..Make sure you understand what machine learning is and its three key areas..Click to read:Machine Learning In 8 MinutesMachine learning is the present and the future..All technologists, data scientists and financial experts can benefit…medium.com2..Choose your target language..Get familiar with Python..Click to read:Python From ScratchPython is one of the most popular programming language for data analysis and Machine Learning..Additionally a large…medium.comLet’s Start The Implementation1.. More details

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