If we had to summarize 2025 in one sentence, it would be: The year we moved from “Prompts” to “Systems.”

MLPills is a dedicated platform for machine learning enthusiasts, data scientists, and AI practitioners seeking  tutorials, case studies, and resources on artificial intelligence and machine learning. With a focus on practical applications and real-world examples, MLPills covers a wide range of topics, including supervised and unsupervised learning algorithms, deep learning architectures, natural language processing, and computer vision. By providing step-by-step guides and code samples, MLPills empowers learners to explore complex concepts and implement machine learning solutions in their projects and applications.

Machine Learning Pills

2025 marked a shift from simple prompts to complex AI systems. The year covered five learning paths: building autonomous agent systems with orchestration and structured outputs, mastering RAG pipelines with advanced retrieval and reranking, understanding time series forecasting with stationarity and Bayesian methods, revisiting fundamental ML algorithms with interpretability tools like SHAP, and focusing on data engineering fundamentals including EDA, handling imbalanced datasets, and A/B testing. The evolution moved from basic chatbots to production-ready agentic workflows with memory, tool use, and multi-step reasoning.

MLPills - Year in Review 2025

🧠 Path 4: The ML Practitioner (Back to Basics)

🛠️ Path 5: Data Strategy, EDA & Engineering