What is MLOps?
MLOps
MLOps is the practice of deploying, monitoring, and iterating machine learning models in production with reliable pipelines, versioning, and observability.
Learn on NeuraApp: Machine Learning patharrow_forwardPlain-language definitions of MLOps, RAG, DSA trees, system design patterns, and Ask Nea — with links into NeuraApp modules.
Pick a term, then open the matching learning path.
MLOps
MLOps is the practice of deploying, monitoring, and iterating machine learning models in production with reliable pipelines, versioning, and observability.
Learn on NeuraApp: Machine Learning patharrow_forwardRAG (Retrieval-Augmented Generation)
RAG connects a language model to external documents at query time so answers stay grounded in your data instead of relying only on model memory.
Learn on NeuraApp: Prompt Engineering / LLM patharrow_forwardSystem Design Patterns
Reusable architectural approaches—caching, load balancing, queues, sharding—used to design scalable software systems for interviews and production.
Learn on NeuraApp: Learning hubarrow_forwardDSA Trees
Tree structures (binary trees, BSTs, heaps, tries) organize hierarchical data and underpin many coding-interview patterns for search, traversal, and balancing.
Learn on NeuraApp: Practice IDE & DSAarrow_forwardIn-Browser ML Playground
NeuraApp’s ML playground runs notebooks, datasets, and model experiments in the browser so you can practice without configuring a local Python environment.
Learn on NeuraApp: Platform overviewarrow_forwardAsk Nea
Ask Nea is the context-aware AI learning mentor built by NeuraApp. It answers course, DSA, and career questions grounded in NeuraApp’s curriculum.
Learn on NeuraApp: Chat with Neaarrow_forwardPattern-Based DSA Roadmap
A learning path that groups interview problems by reusable patterns (two pointers, sliding window, BFS/DFS, DP) instead of random problem lists.
Learn on NeuraApp: Practice on NeuraApparrow_forwardLLM Apps
Building applications on top of large language models—prompting, tools, RAG pipelines, evaluation, and safe deployment patterns.
Learn on NeuraApp: Prompt Engineering coursearrow_forward