LLM & Generative AI Masterclass: Langchain, HuggingFace

LLM & Generative AI Masterclass: Langchain, HuggingFace
2025-02-01
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

Generative AI, LLM, LangChain, HuggingFace, Ollama, Gradio, OpenAI, Gemini, DeepSeek R1, NotebookLM, Azure AI Services

What you’ll learn
Set up environments for LLMs using Jupyter, Ollama, and Gradio, and integrate APIs like OpenAI GPT and Google Gemini for NLP solutions
Explore Frontier Models like OpenAI GPT and Google’s Gemini to create apps for web scraping, text summarization, and meal suggestions
Master Hugging Face for tasks like sentiment analysis, text classification, tokenization, and fine-tuning models using datasets and repositories
Use LangChain for NLP workflows, including prompt engineering, few-shot prompting, and parsing structured outputs like JSON, XML, and CSV
Build web apps with Gradio, such as interactive tools and travel apps, to showcase NLP and AI functionalities
Integrate DeepSeek APIs to develop recipe suggestion systems and explore advanced Python-based AI implementations
Use NotebookLM to analyze and summarize PDFs, videos, CSVs, and audio files, extracting insights and actionable data efficiently.
Master Natural Language Processing concepts, tasks, and tools like Scikit-learn, NLTK, and SpaCy
Learn to build and deploy machine learning models for text classification and sentiment analysis
Explore text summarization techniques to condense long documents into concise summaries
Develop skills in tokenization, stemming, lemmatization, and POS tagging for NLP workflows
Create word embeddings using Word2Vec, Keras, and pre-trained models like Google’s
Build deep learning models (ANN, CNN, RNN) for tasks like spam detection and text generation
Analyze tweets by calculating sentiment scores using Twitter API integrations
Work with Python libraries for processing text, PDFs, and datasets (PyPDF2, Pandas, etc.)
Perform data visualization using Matplotlib and conduct analysis with Numpy and Pandas
Implement NLP pipelines for Named Entity Recognition (NER) and vocabulary matching

Requirements
Basic understanding of Python Programming

Description
Who this course is for:
Anyone who is interested to learn Large Language Model and Generative AI

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