AI and data science are advancing at a lightning-fast pace with new skills and applications popping up left and right. At ODSC East this April 23-25 you’ll find hands-on instruction, featuring real-world use cases and practical examples, that will enable you to put your new skills to good use immediately. Check out just a few of the sessions you’ll find at the can’t-miss conference of the year.
Deep Learning with PyTorch and TensorFlow
Dr. Jon Krohn | Chief Data Scientist | Nebula.io
Join one of the best and brightest minds in Deep Learning, and bestselling author of Deep Learning Illustrated, Dr. Jon Krohn, for an immersive introduction to Deep Learning that brings high-level theory to life with interactive examples featuring all three of the principal Python libraries, PyTorch, TensorFlow 2, and Keras.
By the end of the session, you’ll be equipped with the foundational knowledge needed to train Deep Learning models following all of the latest best practices.
NLP with GPT-4 and other LLMs: From Training to Deployment with Hugging Face and PyTorch Lightning
Dr. Jon Krohn | Chief Data Scientist | Nebula.io
Hear from one of the leading experts in Large Language Models, Dr. Jon Krohn as he takes a deep dive into the models like GPT-4 that are transforming the world in general and the field of data science in particular at an unprecedented pace.
You’ll explore the breadth of capabilities of state-of-the-art LLMs like GPT-4 can deliver through hands-on code demos that leverage the Hugging Face and PyTorch Lightning Python libraries.
Ben Needs a Friend – An intro to building Large Language Model applications
Benjamin Batorsky, PhD | Data Science Consultant
Calling all introverts! Ditch all your tedious social plans and learn how to make your own AI friend powered by Large Language Models in this tutorial from Benjamin Batrosky.
In this session, you’ll cover some of the essential topics in LLM development, including prompt engineering and fine-tuning, document embeddings, Retrieval-Augmented Generation (RAG), and LangChain and Transformers libraries. By the end of the tutorial, you’ll have a basic familiarity with how to use the latest tools for LLM development.
Aligning Open-source LLMs Using Reinforcement Learning from Feedback
Sinan Ozdemir | AI & LLM Expert, Author, Founder + CTO | LoopGenius
Delve into the world of fine-tuning Large Language Models (LLMs) for optimal human interaction in this ODSC East 2024 session. You’ll cover core concepts, with a focus on reinforcement learning techniques, and get hands-on, practical experience in data preprocessing, quality assessment, and implementing reinforcement learning techniques for manual alignment.
By the end of the session, you will be well-equipped to harness the power of open-source LLMs effectively and to tailor your models to meet the specific demands of your industry or domains.
Productionizing AI and LLM Apps with Ray Serve
Adam Breindel | Technical Instructor | Anyscale
Kamil Kaczmarek | Technical Training Lead | Anyscale
Designing and training an AI/ML application is just the beginning of the project. Successful AI-powered services are resilient and efficient, scalable to demand, adaptable to heterogeneous environments, and able to integrate different services.
In this session, you’ll learn to use Ray Serve to compose online inference applications meeting all of the above requirements and more. You’ll build services that integrate with each other while autoscaling individually, even supporting individual hardware and software requirements — all using regular Python and often with just one new line of code.
Introduction to scikit-learn: Machine Learning in Python
Thomas J. Fan | Senior Machine Learning Engineer | Union.ai
Unfamiliar with Scikit-learn? Join this session with renowned expert Thomas J. Fan, for a comprehensive introduction to this widely-used Python machine learning library used by data science practitioners from many disciplines.
You’ll explore scikit-learn’s API for supervised machine learning, which primarily consists of three methods: fit to build models, predict to make predictions from models, and transform to modify data. This consistent and straightforward interface helps to abstract away the algorithm, thus allowing us to focus on our domain-specific problems.
And continue on to topics like testing data and model evaluation, preprocessing techniques, Pandas output API, the Pipeline, and Gradient Boosting. After this training, you will have the foundations to apply scikit-learn to your machine learning problems.
LLMs Meet Google Cloud: A New Frontier in Big Data Analytics
Mohammad Soltanieh-ha, PhD | Clinical Assistant Professor | Boston University
Dive into the world of cloud computing and big data analytics with Google Cloud’s advanced tools and big data capabilities. Designed for industry professionals eager to master cloud-based big data tools, this workshop offers hands-on experience with various big data analytics tools, such as Dataproc, BigQuery, Cloud Storage, and Compute Engine. You will also dive into the new LLM capabilities of Google Cloud, with an exploration of how these innovative AI models can extract deeper insights, generate creative text, and automate large-scale tasks, taking your big data analysis to the next level.
Don’t miss this chance to build new skills for a rapidly changing world defined by AI and Machine Learning applications at ODSC East 2024. Register now–50% off ends soon.