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Pursuing my own Machine Learning Degree

Writer: JJ CruzatJJ Cruzat

Updated: Oct 28, 2023

Earning Peso but degrees were in Dollars so might as well make my own :)


Note: The upper section of this blog post is for updates. This is an updated blog about my continuous learning journey.

Updates:

2021-10-01| Started to write my Blog about learning machine learning. About me, My goals, Why Machine learning. My Machine Learning learning Journey

About Me

I'm Sergei Cruzat and I'm 25 years old as of this writing

I live in Laguna Philippines and I loathe our corrupt government :D

I'm a Licensed Mechanical Engineer but have shifted my career to Data Analytics

Currently, I'm working for Fortune 500 company as a Data Analyst

I write poems and perform original songs and firm believer of

"Love is best communicated thru songs and poetry" ;)

I'm an advocate of green energy and I believe there is climate change( Fight me haha)


My Goals

In the long run, I want to be an expert and consultant in the field of Data Science. Implementing it in various fields like Manufacturing, Energy, and the Government. I also want to mentor other professionals about data science on how to implement it and integrate it. For my short term goals, I want to officially be a machine learning engineer and be on my merry way :)


Specific Goals/Dreams I have are:

  1. Create a Predictive Maintenance model

  2. Create a Quality Detection Model

  3. Sales Prediction/Forecasting

  4. Become one of the advocates with intertwining Mechanical engineering to ML

  5. Teach on how to learn Machine learning intelligently


Why learn Machine Learning?

For one, it is one of the hottest and in-demand jobs on the market today. Almost 30% of managers in the US are already using AI and Machine learning in their work and about another 50% are planning to integrate within 3 to 5 years from now in the ongoing 4th industrial revolution. I'm all in for making life-improving products easier to use, faster and accessible to all!


Job security aside, I personally chose to do machine learning because it is convenient & non-discriminatory and you can start innovation on your own. Let me expound on these three reasons:

  1. Passive Discrimination: I live in a third-world country wherein our professionals are somewhat downgraded from their first-world counterparts(If you are working in an international company). Decisions and Plans are often not supported (Priority wise, and execution-wise) and sent to the back of the line just because the perception of Engineering prowess is based on educational achievement in what country. But Machine learning does not discriminate. You can learn from the internet and show your projects as proof of skills and knowledge and (almost) no one will question it. It is

  2. Convenience: Convenient in terms of working remotely. Doing Data Analytics and Machine learning paves way for international opportunities without working away from home.

  3. Starting Innovation: You can start with your great ambition with just a laptop or PC and be on the way to showing the world what you are aiming for! No need for immediate investment or support you just have to start to get that support.


Finally!

My own Machine learning Pathway

Inspired by Daniel Bourke, Ken Jee, and other youtube mentors

I structured this degree with 3 succeeding parts the Foundational, Advance bit, and Projects in between. For Foundational I'm deep-diving into the python language and knowing what computer science & data science are in general. After equipping myself with the basic skill set and knowledge to initiate an ML project, I will get to know more about machine learning concepts and frameworks especially on predictive analysis which I hope I can master. After the Foundational stage will be a Python project in ETL and Exploratory Analysis. For Advance is a predictive python project that I will, later on, decide on, possibly regarding sales forecasting because I'm a sales analyst as of the moment. The last project to seal the deal would be a machine learning app on a mobile device. My Strategy in assigning the courses I learned was firstly cost, can't get enough of those free courses! Then if there are gaps within the knowledge needed to build my projects then I would look for paid ones. But one key to learning effectively is to try and try until what you learned is engraved in you.


Foundational Courses:



Advance Courses:




Books:


-Hands-on Machine learning with Sickit-learn and TensorFlow by Aurelian Geron


Extras:


Web Development:

Capstone Projects:

These will be a placeholder for now guys!

Foundational:

Advance:

Final:

What's next?


Graduation! I will let you know my next steps after actually doing all these. I will surely update this once I've finished my projects and if ever I made it :)









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