👋 Hi, I'm @carlosrod723!

• 🤖 Passionate about AI, machine learning, and deep learning.
• 🌱 Actively expanding my knowledge in:
  • Python & its ML libraries (NumPy, Pandas, Scikit-learn, Tensorflow, etc.)
  • ML models and concepts
  • Cloud ML platforms (AWS SageMaker, GCP Vertex AI)
  • Statistics pertinent to ML
  • SQL
  • The entire ML workflow
• 💼 Eager to apply my skills to real-world projects and open to new opportunities.
• 📫 Let's connect! carlos.rodriguezacosta@gmail.com

Promtp- Hello chatGPT. What do you know about me that I may not know about myself based on all of our interactions?

ChatGPT said: ChatGPT:

Hello, Carlos! Based on our interactions, here are some observations that might offer you a fresh perspective or remind you of things you might not have fully reflected on:

Consistency in Learning: You have a consistent pattern of carefully refining your work, especially when it comes to machine learning, R Shiny, and data analysis projects. You prefer taking things one step at a time, checking every code block, and avoiding undefined variables or elements to ensure everything works smoothly.

Adaptive Problem-Solving Approach: You tend to restart or rework parts of projects if you're not satisfied with their performance. For example, during the Shinkansen hackathon, you completely restarted your notebook and tried different models when the initial approach didn't yield the expected results.

Attention to Professional Presentation: Whether it's creating stunning visualizations in Tableau, meticulously organizing your GitHub repositories, or ensuring high-quality final submissions, you place a strong emphasis on the professional presentation of your work.

Openness to Tools: You’re not afraid to explore new tools or approaches—like shifting from PyTorch to different frameworks depending on the project—but you also know when not to overcomplicate things (such as choosing not to use PyTorch for certain projects when it wasn’t necessary).

Balance of Patience and Urgency: You often exhibit patience when working on long-term goals (such as gradually improving a model), but you're also comfortable applying urgency when necessary, especially in meeting client deadlines or finalizing projects like the RiskMiner algorithm or the school dropout prediction project.

Creative and Adaptive Vision: From using Weighted Voting and Stacking methods in ensemble models to creating climate data viewers in R Shiny, you’ve shown that you’re not just technically skilled but also creative in applying techniques to different problem domains.

Diverse Skill Set: You have a unique combination of skills across multiple domains—machine learning, data visualization, MLOps, NLP, and even civil engineering. This diverse skill set allows you to approach problems from different angles and makes you adaptable to various projects, from predictive modeling to real-time applications like the RiskMiner project or the sentiment analysis using Twitter tweets.

Client-Centered Focus: You show a strong ability to understand and adapt to client needs. Whether it's refining your work based on feedback or restructuring projects to meet expectations, your client-first approach is evident in your careful attention to detail, such as implementing features like intermediate rewards in RiskMiner or tailoring visualizations for your school dropout analysis. This ability to listen and deliver what clients need sets you apart.

Long-Term Strategic Thinking: You’re strategic not just in how you approach immediate problems but also in how you position yourself for future opportunities. You keep your profiles updated (like on Upwork and GitHub), constantly adding new skills and showcasing them through carefully constructed projects. This forward-thinking approach shows you're focused on growth and expanding your career, not just ticking off tasks.

Comfort with Complexity: Whether working on complex algorithms for alpha discovery in finance or creating custom packages in R for spatial analysis, you're comfortable diving deep into challenging problems. You embrace complexity rather than shy away from it, which is a rare and valuable trait in fields like machine learning and AI.

Commitment to Mastery: You’re always refining your craft. Even after completing a project, you seem open to reworking or starting fresh to improve performance, as seen in your approach to the Shinkansen hackathon and RiskMiner. This commitment to mastery, rather than settling for "good enough," shows your dedication to not just delivering but excelling.

Vision for Scalability: Many of your projects, such as ZenFlow AI and the Telecom Churn project, suggest that you think about scalability and automation. You design your solutions with a larger impact in mind, considering how tools and models can be used in real-world applications and by broader audiences.

Python	R

NumPy	Pandas	SciPy	Matplotlib	Seaborn	scikit-learn	TensorFlow	Keras	Statsmodels	PyTorch

ggplot2	dplyr	tidyr	readr	caret	randomForest	xgboost	Shiny
				caret 🌟	randomForest 🌲

Jupyter	Google Colab	PostgreSQL	BigQuery	Kaggle	Posit Cloud
			BigQuery 📊

Amazon Web Services	Google Cloud Platform	Microsoft Azure