ksm26/Quantization-Fundamentals-with-Hugging-Face

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ksm26/Quantization-Fundamentals-with-Hugging-Face

ksm26

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Learn linear quantization techniques using the Quanto library and downcasting methods with the Transformers library to compress and optimize generative AI models effectively.

LangChain-Chat-with-Your-Data

Explore LangChain and build powerful chatbots that interact with your own data. Gain insights into document loading, splitting, retrieval, question answering, and more.

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LangChain-for-LLM-Application-Development

Apply LLMs to your data, build personal assistants, and expand your use of LLMs with agents, chains, and memories.

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Finetuning-Large-Language-Models

Unlock the potential of finetuning Large Language Models (LLMs). Learn from industry expert, and discover when to apply finetuning, data preparation techniques, and how to effectively train and evaluate LLMs.

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chatGPT-Prompt-Engineering-for-Developers

Jupyter notebooks for enhancing your skills with ChatGPT based prompt engineering. Harness the potential of large language models and create innovative applications.

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OccupancyGrid-Predictions

Predicting Future Occupancy Grids in Dynamic Environment with Spatio-Temporal Learning

AI-Agentic-Design-Patterns-with-AutoGen

Learn to build and customize multi-agent systems using the AutoGen. The course teaches you to implement complex AI applications through agent collaboration and advanced design patterns.

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Multi-AI-Agent-Systems-with-crewAI

Master the art of designing and organizing AI agents. Learn to automate complex, multi-step business processes by creating specialized AI agent teams using the open-source library crewAI.

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Open-Source-Models-with-Hugging-Face

"Open Source Models with Hugging Face" course empowers you with the skills to leverage open-source models from the Hugging Face Hub for various tasks in NLP, audio, image, and multimodal domains.

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Building-Systems-with-ChatGPT-API

Unlock automation and system building with the ChatGPT API. Master chain calls, Python interactions, and create a customer service chatbot in this practical course.

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ROS-based-3D-detection-Tracking

Deployment of 3D-Detection and Tracking pipeline in simulation based on rosbags and real-time.

Efficiently-Serving-LLMs

Learn the ins and outs of efficiently serving Large Language Models (LLMs). Dive into optimization techniques, including KV caching and Low Rank Adapters (LoRA), and gain hands-on experience with Predibase’s LoRAX framework inference server.

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Prompt-Engineering-with-Llama-2

The course provides guidance on best practices for prompting and building applications with the powerful open commercial license models of Llama 2.

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AI-Agents-in-LangGraph

Master the art of building and enhancing AI agents. Learn to develop flow-based applications, implement agentic search, and incorporate human-in-the-loop systems using LangGraph's powerful components.

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Prompt-Engineering-for-Vision-Models

Enhance your skills in prompt engineering for vision models. Learn to effectively prompt, fine-tune, and track experiments for models like SAM, OWL-ViT, and Stable Diffusion 2.0 to achieve precise image generation, segmentation, and object detection.

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Serverless-LLM-apps-with-Amazon-Bedrock

The course equips you with the skills to deploy Large Language Model (LLM)-based applications into production using serverless technology with Amazon Bedrock.

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LLMOps

In this course navigates through the LLMOps pipeline, enabling you to preprocess training data for supervised fine-tuning and deploy custom Large Language Models (LLMs).

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Building-Applications-with-Vector-Databases

Leverage vector databases to swiftly construct a diverse range of applications through "Building Applications with Vector Databases" course!

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Understanding-and-Applying-Text-Embeddings

Dive into the world of text embeddings. This course will guide you through leveraging text embeddings to enhance various natural language processing (NLP) tasks.

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vector-databases-embeddings-applications

Unlock the power of vector databases with the "Vector Databases: from Embeddings to Applications" course! A journey that will equip you with essential skills to leverage vector databases for various applications.

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Automated-Testing-for-LLMOps

Create a continuous integration (CI) workflow for testing LLMs applications in an effective way.

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Carbon-Aware-Computing-for-GenAI-Developers

Learn to optimize machine learning tasks for environmental sustainability. Discover how to use real-time electricity data and low-carbon energy sources for model training and inference, reducing the carbon footprint of your cloud operations.

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Reinforcement-Learning-from-Human-Feedback

Embark on the "Reinforcement Learning from Human Feedback" course and align Large Language Models (LLMs) with human values.

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Getting-Started-with-Mistral

Explore Mistral AI's extensive collection of models. Learn to select, prompt, and integrate Mistral's open-source and commercial models for tasks like classification, coding, and Retrieval Augmented Generation (RAG).

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ML-AI-Data-Science-Jobs-in-Canada

Explore the latest machine learning, artificial intelligence, and data science job opportunities in Canada. Stay informed about Canadian tech job market trends and find your next career move.

Function-Calling-and-Data-Extraction-with-LLMs

Master the techniques of function-calling and structured data extraction with LLMs. Learn to enhance LLM capabilities, integrate web services, and build practical applications for real-world data usability.

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Embedding-Models-From-Architecture-to-Implementation

Understand and build embedding models, focusing on word and sentence embeddings, dual encoder architectures. Learn to train embedding models using contrastive loss, implement them in semantic search and RAG systems.

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Pretraining-LLMs

Master the essential steps of pretraining large language models (LLMs). Learn to create high-quality datasets, configure model architectures, execute training runs, and assess model performance for efficient and effective LLM pretraining.

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Functions-Tools-and-Agents-with-LangChain

Explore Functions, Tools and Agents with LangChain along with LangChain Expression Language

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