Natural Language Processing with Probabilistic Models

This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers. You'll acquire critical MLOps skills, including the use of Python and Rust, utilizing GitHub Copilot to enhance productivity, and leveraging platforms like Amazon SageMaker, Azure ML, and MLflow. You'll also learn how to fine-tune Large Language Models (LLMs) using Hugging Face and understand the deployment of sustainable and efficient binary embedded models in the ONNX format, setting you up for success in the ever-evolving field of MLOps Through this series, you will begin to learn skills for various career paths: 1. Data Science - Analyze and interpret complex data sets, develop ML models, implement data management, and drive data-driven decision making. 2. Machine Learning Engineering - Design, build, and deploy ML models and systems to solve real-world problems. 3. Cloud ML Solutions Architect - Leverage cloud platforms like AWS and Azure to architect and manage ML solutions in a scalable, cost-effective manner. 4. Artificial Intelligence (AI) Product Management - Bridge the gap between business, engineering, and data science teams to deliver impactful AI/ML products. Applied Learning Project Explore and practice your MLOps skills with hands-on practice exercises and Github repositories. 1. Building a Python script to automate data preprocessing and feature extraction for machine learning models. 2. Developing a real-world ML/AI solution using AI pair programming and GitHub Copilot, showcasing your ability to collaborate with AI. 4. Creating web applications and command-line tools for ML model interaction using Gradio, Hugging Face, and the Click framework. 3. Implementing GPU-accelerated ML tasks using Rust for improved performance and efficiency. 4. Training, optimizing, and deploying ML models on Amazon SageMaker and Azure ML for cloud-based MLOps. 5. Designing a full MLOps pipeline with MLflow, managing projects, models, and tracking system features. 6. Fine-tuning and deploying Large Language Models (LLMs) and containerized models using the ONNX format with Hugging Face. Creating interactive demos to effectively showcase your work and advancements.

You're here, so you've probably heard about ChatGPT and how it's going to change the world. This course is designed for those who are interested in leveraging A.I ChatGPT in their specific domain or niche. Whether you're a marketer, business strategist, finance professional, teacher or student, or a creative artist - this course goes over dozens of examples on how to get the most out of ChatGPT. Even if you're a writer, or a tradesperson - this class can still be of great use to you. The entire world will use this tool within a matter of months. Chat GPT already is changing the world, and increasing the productivity of those who can best use it. "Leverage" is the key word here, and in this course my attempt is to share as many possible forms of maximizing the output A.I can give you. Whether that's through your existing business or career, or you want to discover new and creative ways to increase your income - this course covers many things. We live in a digital information Era, and ChatGPT is a way to interact with text/data that has never existed before. ChatGPT has more signups in a month than some of the top services like Facebook had in months. In this class, I share my mental framework for thinking about how to interact with ChatGPT A.I, as well as numerous examples that include: - Multiple ideas for Leveraging A.I for income generation (A.I Arbitrage Opportunities) - E-Commerce Tactics to Speed up your workflows - Leveraging A.I for creative art direction (Filmmakers, Artists, Art Directors, Creative Directors, Book Writers) - SEO Strategies and Advertising Strategies for all online businesses - How to create contracts and emails within seconds (the right way) - How to "Compress" and "Decompress" information selectively - Using A.I to create simple snippets code, to speed up your workflows (Even if you aren't a coder!) - Using AI for software specific problems - Using AI for Writing, Using AI to correct Writing - Using A.I for students writing, and teachers needing to create content around courses - Using A.I to discover what you don't know (Extremely useful.) - Using A.I to help learn languages - Understanding Iteration, and why ChatGPT is not Google. - How to follow the latest technological trends, who to follow - and knowing where to look. If you hear things from the news, you're already late. - Mixing Chat GPT with AI Text-to-Image Art Generation, using Midjourney or Stable Diffusion - Understanding how an A.I Chatbox works versus a search engine - Using Chat GPT to create personalized fitness plans - Using Chat GPT to deliver compelling sales pitches

This IBM course will teach you how to implement, train, and evaluate generative AI models for natural language processing (NLP). The course will help you acquire knowledge of NLP applications including document classification, language modeling, language translation, and fundamentals for building small and large language models. You will learn about converting words to features. You will understand one-hot encoding, bag-of-words, embedding, and embedding bags. You also will learn how Word2Vec embedding models are used for feature representation in text data. You will implement these capabilities using PyTorch. The course will teach you how to build, train, and optimize neural networks for document categorization. In addition, you will learn about the N-gram language model and sequence-to-sequence models. This course will help you evaluate the quality of generated text using metrics, such as BLEU. You will practice what you learn using Hands-on Labs and perform tasks such as implementing document classification using torchtext in PyTorch. You will gain the skills to build and train a simple language model with a neural network to generate text and integrate pre-trained embedding models, such as word2vec, for text analysis and classification. In addition, you will apply your new skills to develop sequence-to-sequence models in PyTorch and perform tasks such as language translation.