In this video, we will discuss how you can approach NLP, the step-by-step process you should follow, the resources you can refer to, and the kind of problems you can solve with NLP knowledge. Step 1: Text Pre-Processing Step 2: Text Representation Step 3: Information Extraction Step 4: Deep Learning for NLP Step 5: Transformers and Transfer Learning Step 6: Deploying NLP Models Step 7: Embedding and Semantic Search Step 8: Large Language Models (LLMs) Step 9: Vector databases Step 10: LLM Libraries: LangChain: Your One-Stop Shop for LLM Applications Llama Index: A Flexible Library for Data Augmentation and Indexing Step 11: MLOps for NLP Step 12: Relational Databases and SQL NLP Roadmap Resources: AI Demos: is your go-to directory for video demos of the latest AI tools. AI Demos's goal is to educate and inform about the possibilities of AI. NLP Playlist: 🚀 Top Rated Plus Data Science Freelancer with 8 years of experience, specializing in NLP and Back-End Development. Founder of FutureSmart AI, helping clients build custom AI NLP applications using cutting-edge models and techniques. Former Lead Data Scientist at Oracle, primarily working on NLP and MLOps. 💡 As a Freelancer on Upwork, I have earned over $100K with a 100% Job Success rate, creating custom NLP solutions using GPT-3, ChatGPT, GPT-4, and Hugging Face Transformers. Expert in building applications involving semantic search, sentence transformers, vector databases, and more.
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