Data Mining & Modeling to Mechanics of Deployment, Monitoring & Automated Closed-Loop Retraining скачать в хорошем качестве

Data Mining & Modeling to Mechanics of Deployment, Monitoring & Automated Closed-Loop Retraining

At the heart of this transformation is the data science lifecycle, a comprehensive framework that governs the journey of a data point from its raw structural representation to its eventual role as a feature in a deployed model. While early iterations of this lifecycle focused primarily on discovery and modeling, contemporary standards have expanded to encompass the complex mechanics of deployment, monitoring, and the automated closed-loop retraining necessitated by the dynamic nature of real-world data environments. The successful execution of this lifecycle is predicated on a deep mastery of foundational mathematics—encompassing linear algebra, multivariate calculus, and statistical inference—which informs the optimization of models for high-concurrency, low-latency deployment environments. 👉 ⏱️Timestamps: 0:00 - 1. Intro Data Science Life cycles 1:00 - Introduction To Exploratory data analysis 6:12 - 2. Technical Machine Learning Deep Dive & Vector Embeddings 12:00 - Deep Learning 16:54 - Supervised learning Algorithm 24:51 - Unsupervised learning Algorithm 33:24 - Reinforcement learning Algorithm 41:42 - 3. Model deployment and closing thoughts 🎓 Perfect for students, AI enthusiasts, and anyone curious about how machines understand human language.🌍 Animated learning from Africa to the world — Data Science Animated by Lubula. #statistics #ai #datascience #machinelearning #deeplearning #tech