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Know Thyself - The Value and Limits of Self-Knowledge: The Examined Life
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Implement data transformation for an end-to-end machine learning project using pipelines for categorical values, missing values, and scaling.
Deploy an end-to-end machine learning application on AWS with Docker, ECR, EC2, App Runner, and a GitHub Actions CI/CD workflow.
Follow an end-to-end MLOps project that assembles data and prediction pipelines, then deploys the system on AWS with GitHub Actions.
Demonstrates how to monitor machine learning models, check their performance, and detect target drift with Evidently AI.
A hands-on machine learning project follows data from cleaning and exploratory analysis through feature selection, model training, and hyperparameter tuning.
Build and serve machine learning models with BentoML, demonstrate a model API through Swagger, and package the application as a Bento.
An overview of ChatGPT’s three training stages: generative pretraining, supervised fine-tuning, and reinforcement learning from human feedback.
Build a text summarization project from data ingestion through model evaluation, a prediction app, and CI/CD deployment on AWS.
Build a chicken disease classifier end to end, tracking its pipeline with DVC and deploying it to AWS and Azure through GitHub Actions.
A focused refresher connects the linear regression cost function to convergence algorithms across simple and multiple regression.
Learn to detect anomalous observations with Isolation Forest, DBSCAN, and Local Outlier Factor, including practical implementations.
Learn to containerize and package an end-to-end data science project with Docker, from images and installation to pushing images and using Docker Compose.
Build a machine learning project by defining the problem, exploring and engineering data, training a model, and organizing the code modularly.
Learn heap data structures from complete binary trees through min- and max-heap operations, heap sort, complexity analysis, and interview problems.
Explains bubble, selection, and insertion sort through array-based classifications, step-by-step implementations, and sorting behavior.
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