Seeking guidance and resources to enhance my practical hands-on experience in building ML pipelines and scalable ML/DL models using Python and other environments. I'm also interested in learning about AWS services related to pipelines, just enough to connect the dots & read the architecture diagrams etc. Any guidance, coaching, or suitable resources would be greatly appreciated! I've tried platforms like Coursera but need more targeted help to progress further. While I have 10 years of experience & recently joined the company and can code in Python, I lack resources with the right depth. Ideally, I'd love to have a buddy or teacher to engage in discussions, exchange ideas, review code, and work together on executing projects. Having a companion would keep me motivated and consistent in my learning journey as well as organized since there is plethora of info out there. I don’t know how to go about it, suggestions are welcome. Willing to pay for such guidance and support. Thank you for your help!! #data #dataanalytics #datascience #AWS #MachineLearning #Retail #Finance #Banking
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Lmao, why do you mention coding in python. Thats not what data science is
For example- The use of classes etc can greatly improve the organization of modules & project etc.