📚https://pratimuniyal.gumroad.com/l/BuildinganLLMOpsPipelineUsingHuggingFace

Thank you, everyone, for your invaluable feedback and support for my previous two books:
📚 AWS for System Administrators: https://www.amazon.com/AWS-System-Administrators-automate-infrastructure/dp/1800201532
📚 Cracking the DevOps Interview: https://pratimuniyal.gumroad.com/l/cracking-the-devops-interview

I'm thrilled to announce the release of my new book, Building an LLMOps Pipeline Using Hugging Face. In a world where Generative AI and large language models (LLMs) are transforming our daily lives, many of us use tools like ChatGPT regularly; this book serves as a comprehensive guide to mastering LLMOps within the Hugging Face ecosystem.

Starting with the fundamentals of machine learning and deep learning, the book introduces key concepts, types of learning, and various machine learning models. It is designed to provide readers with both the knowledge and practical skills needed to leverage the power of LLMOps effectively.
You can find the book link here.
📚https://pratimuniyal.gumroad.com/l/BuildinganLLMOpsPipelineUsingHuggingFace

Book Breakdown
1️⃣ Chapter 1: Foundations of Machine Learning and Deep Learning
Introduction to the fundamental concepts, types, and applications of machine learning and deep learning.
2️⃣ Chapter 2: Exploring Hugging Face: Tools, Features, and Integration for Machine Learning
Overview of Hugging Face's tools and resources for implementing and fine-tuning machine learning models.
3️⃣ Chapter 3: Mastering Transformers and Datasets with Hugging Face
Exploration of transformer models and datasets in Hugging Face, focusing on their architecture and practical use.
4️⃣ Chapter 4: Text Generation and Classification with Hugging Face Transformers
Guide to using Hugging Face's Transformers library for text generation, classification, and summarization tasks.
5️⃣ Chapter 5: Creating Pipelines for Image, Audio, and Video Processing with Hugging Face
Instruction on building pipelines for image, audio, and video processing using Hugging Face tools.
6️⃣ Chapter 6: Document and Visual Question Answering in Multi-Modal Tasks with Hugging Face
Discussion on setting up document and visual question answering pipelines for multi-modal tasks.
7️⃣Chapter 7: Fine-Tuning a Pre-Trained Model for Sentiment Analysis with Hugging Face
Step-by-step guide to fine-tuning a pre-trained model for improved sentiment analysis performance.
8️⃣Chapter 8: Project: MLOps, AIOps, LLMOps, and Deploying an Application with GitHub Actions and AWS EKS
Practical guide to setting up a CI/CD pipeline for deploying a machine learning application using GitHub Actions and AWS EKS.
9️⃣ Chapter 9: Next Steps with Hugging Face: Contributing, Collaborating, and Continuous Learning
Encouragement and guidance for contributing to the Hugging Face community and continuing the learning journey.

I'm looking forward to your feedback 🙏🙏🙏