🧪 Phase 7: Integration Testing
The final touch: integration testing for all pipelines! Ensuring smooth functionality between training, deployment, and monitoring 🚦. #MLOpsZoomcamp #DataTalksClub

📊 Phase 6: Model Monitoring
Set up the monitoring pipeline for detecting data and model drift with Evidently 🔎. Grafana dashboards are live, and I’m tracking model performance in real time! #MLOpsZoomcamp #DataTalksClub

🚀 Phase 5: Deploying the Model
Deploying the model using BentoML 🧑‍💻. Serving it as a scalable API in Docker for production. Everything is automated and ready to go live! #MLOpsZoomcamp #DataTalksClub

⚙️ Phase 4: Model Training Pipeline
Finalizing the training pipeline for my optimized model 🏅. It’s now tracked in MLflow and promoted to production! Let’s prepare it for deployment. #MLOpsZoomcamp #DataTalksClub

🛠️ Phase 3: Tech Stack Setup
All set up with ZenML, MLflow, Optuna, and Docker-Compose for this MLOps project 🧰. Now the integration begins for seamless pipeline orchestration and experiment tracking! #MLOpsZoomcamp #DataTalksClub

🔧 Phase 2: Model Training & HPO
Feature engineering and model training in full swing! Using XGBRegressor for bike trip predictions 🚴 and optimizing with Optuna to get the best-performing model. #MLOpsZoomcamp #DataTalksClub

🌍 Phase 1: Data Exploration
Kicking off my MLOps journey by exploring CitiBike and weather data in NYC 🌧️. Performing some EDA and cleaning the dataset to build the foundation for my prediction model of bike trips. #MLOpsZoomcamp #DataTalksClub

Putting everything to the test by evaluating a dataset using hit rate, MRR, and different approaches like Minsearch and Qdrant. 🧪 Can't wait to see how they perform! 📊 #LLMZoomcamp #DataTalksClub

Experimenting with Qdrant to perform efficient vector searches. 🔎 It’s a game-changer for building fast and accurate search pipelines in LLMs. ⚡ Time to compare this approach with others! #LLMZoomcamp #DataTalksClub

Learning about hit rate, MRR, and other evaluation metrics for LLMs. 📈 These metrics will help us measure how well the model retrieves relevant information. 🔍 Exciting stuff! #LLMZoomcamp #DataTalksClub