Proud to officially add the AWS Certified Machine Learning Engineer - Associate certification to my toolkit!
Building robust machine learning pipelines and scaling AI workloads securely on the cloud has always been a key focus of mine. Earning this certification has been a great deep-dive into mastering AWS ML infrastructure, MLOps best practices, and production-grade architectures.
Ready to bring these advanced capabilities to upcoming data science and engineering projects! Let's build something impactful. 💡💪
Congratulations on earning the AWS Machine Learning Engineer certification, Hazem khaled! Robust pipelines and cloud automation make all the difference for production-grade AI systems.
For a local workshop I'd keep the scroll bike for the hero and make the service sections quick to scan. The "what does my bike need" flow is the part that could actually bring bookings.
This is a customer support chatbot that help users to sell their products online.
User will chat with on your website.
It collect leads on your behalf gather detail in a google sheet.
It will even create meeting add to your Google calendar. It is useful for you as an individual, an entrepreneur, as somebody delivery services or product.
I use my niece boutique as a reference.
Tools:
Ai Agent, Ai chat model, memory, code tools, Google sheet and Google calendar.
Ai Agent: as Ai agent you it a task, it will use several tools at it's disposal to respond and act based on the system prompt.
Ai chat model: respond to all the chats.
Memory: you give your agent memory so that it can remember everything read understand and interpret it.
Code tool: It return the days of the week.It gather information about people that are chatting even see them as potential buyers or not.
Google sheet: It record every sales.
Google calendar: You use Google calendar to book an appointment with your customers