Machine Learning & AI
Advanced tutorials and research insights in artificial intelligence
Explore cutting-edge machine learning techniques, deep learning applications, and AI research methodologies. From statistical foundations to advanced neural architectures, these posts cover the essential concepts driving modern artificial intelligence.
Vector Databases, Demystified: From Embeddings to Production-Grade Search
Complete guide to production vector search systems
NEW! Comprehensive deep-dive into vector databases covering embeddings, ANN indexes (HNSW, IVF-PQ), distance metrics, hybrid search, and production deployment. Includes working FAISS implementation achieving 3,334 QPS on 100K vectors with complete code examples and visualizations.
Highlights: Real performance benchmarks • 9 interactive visualizations • Production-ready code • Evaluation metrics • Operational best practices
Multi-Teacher Knowledge Distillation
Advanced AI Techniques for Model Efficiency
Deep dive into state-of-the-art multi-teacher knowledge distillation methods including UEKD, ATMKD, and meta-learning approaches. Learn how to combine the wisdom of multiple AI models into one efficient student model.
T-test Applications
Statistical hypothesis testing fundamentals
Comprehensive guide to T-test applications in data science, covering one-sample, two-sample, and paired T-tests with practical Python implementations.
Top 10 Statistical Concepts in Bioinformatics
Essential statistics for biological data
Deep dive into the most important statistical methods used in bioinformatics research, with real-world examples and computational implementations.
Coming Soon: Neural Architecture Search
Automated ML model design
Explore automated neural architecture search techniques and their applications in optimizing deep learning models for specific tasks.
Topics Covered
Deep Learning
Neural networks, architectures, and advanced techniques
Statistical Methods
Hypothesis testing, regression, and probabilistic models
Research Methods
Experimental design and computational methodologies
Implementation
Python, R, and practical coding tutorials
Stay tuned for more advanced tutorials and research insights in machine learning and artificial intelligence.