CONVERSATION INTO MY MACHINE LEARNING JOURNEY (PART 2)
Continuing from where we left off…. (In case you missed from the beginning, click ==> here to have a taste)
The process began in earnest. The materials for the rock-solid foundation of my building started converging at the site. The likes of:
(i.) Python: acquired this material through the help of a well-known supplier in the industry — Udemy
(ii.) Numpy: acquired this through the same supplier that supplied the Python material — Udemy
(iii.) Pandas: acquired this through the supplier that previously supplied both Python and Numpy
(iv.) SQL{Postgresql}: Udacity extended a hand of fellowship
(v.) Advanced Excel: Udemy came to the rescue. Though, the fundamentals of this material had already been secured even before the conceptualization of the building (Machine Learning).
(vi.) Tableau: Udemy came to the rescue again. (The first phase transited to the second phase from here)
With the rock-solid foundation secured, I sorted help from a contractor (Hamoye), who at the time was on a mission to build lasting skyscrapers from the ground up (training 21st-century Data Scientists through a rigorous process in solving different industry problems with the inclination for growth).
After Hamoye boarded as the contractor, the building processes began in smooth sailing. They started building from the ground floor leveraging on the already secured materials(Python, SQL, Pandas, Numpy, Tableau, etc.). They designed a four-storey building;
(i.) Ground floor — Python for Machine Learning
(ii.) First floor — Machine Learning (Regression)
(iii.) Second floor — Machine Learning (Classification)
(iv.) Third floor — Neural Network-Image Recognition & Objection Detection
(v.) Fourth floor — Practical Time Series Analysis & Forecast
Each floor designed by Hamoye was subsequently evaluated (attached each learning path with a project) together with assessment scores (github repo). After the evaluation processes, there was team collaboration, testing the designs if they met initial structural planning of the building (Capstone Projects in team collaboration). After the contractual timing of the project elapsed, Hamoye hung their boot after building such a glorious edifice of 4-storey building. My learning with Hamoye concluded here…
I know you would be wondering if that was the end of the building processes. Did I stop my ML learning journey? That’s a question that begs for an answer. But remember, I said earlier that this journey is a life-long journey. You’ll get the juicy part of this story in no time. Gracias!!!
