The Ultimate SQL And Databases Guide for 2025 – From Basics to Best Practices
SQL For Beginners: Learn SQL in a practical, beginner-friendly way with real-world examples. Understand how to query, insert, update, and join data in your first hour.
Learn SQL for Beginners: A Practical Introduction to Databases
New to SQL? This beginner-friendly guide breaks down everything from what SQL is to how to write your first query with examples and real use cases.
Understanding Machine Learning From Theory to Algorithms
Master machine learning from theory to practice with detailed explanations of core algorithms, evaluation techniques, and a ready-to-use cheat sheet.
3D Computer Vision: Depth Estimation, Point Cloud Processing, and SLAM
3D computer vision: Learn how to recover depth, process point clouds, and implement SLAM systems to enable 3D understanding in robotics, AR/VR, and autonomous applications.
Deep Learning for Video Analytics: Object Tracking, Action Recognition, and Event Detection
Learn how to build deep-learning pipelines for object tracking, action recognition, and event detection in video. This comprehensive guide covers methods, architectures, datasets, metrics, and deployment best practices.
What is Unsupervised Learning?
Discover What is Unsupervised Learning? how unsupervised learning finds hidden patterns in unlabeled data through clustering, association rules, dimensionality reduction, and anomaly detection.
SQL & Databases 101: Fundamentals of Relational and NoSQL Databases
Learn how to design, query, and optimize both relational and NoSQL databases in this comprehensive guide. Covering SQL basics, advanced techniques, schema design, transactions, and when to choose each database paradigm.
The Ultimate Guide to Artificial Intelligence: Concepts, Applications, and Future Trends
Explore the comprehensive landscape of Artificial Intelligence history, core techniques (ML, deep learning), real-world applications, ethics, tools, and future trends in this comprehensive guide.
MLOps 101: Bringing Machine Learning into Production
MLOps 101: Learn how to operationalize machine learning with MLOps best practices: data ingestion, CI/CD, model deployment, monitoring, and continuous retraining to keep your models reliable and performant.
The Ultimate Guide to Public Datasets for Data Science 2025
Discover how to find, evaluate, and use public datasets for data science projects. This detailed guide covers repositories like Kaggle and UCI, data types (text, image, time series), best practices, domain-specific resources, and real-world case studies.