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Joshua Starmer PhD

Founder and CEO at StatQuest with Josh Starmer and Ex-Lead AI Educator @ Lightning AI

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Dr. Joshua Starmer, the co-founder and CEO of Statsquest and previously working as lead AI educator at Lightning AI, is a distinguished figure in data science and is set to illuminate the stage at DataHack Summit 2024. With a Ph.D. in Biomathematics and an illustrious career spanning academia and industry, Dr. Starmer brings a wealth of expertise to the forefront of analytics. With a passion for translating complex concepts into actionable insights, Dr. Starmer's dynamic presentations promise to empower audiences with cutting-edge knowledge and strategic perspectives. Engage with Dr. Starmer at DataHack Summit to explore the future of data analytics in a transformative way.Dr. Joshua Starmer, the co-founder and CEO of Statsquest and previously working as lead AI educator at Lightning AI, is a distinguished figure in data science and is set to illuminate the stage at DataHack Summit 2024. With a Ph.D. in Biomathematics and an illustrious career spanning academia and industry, Dr. Starmer brings a wealth of expertise to the forefront of analytics. With a passion for translating complex concepts into actionable insights, Dr. Starmer's dynamic presentations promise to empower audiences with cutting-edge knowledge and strategic perspectives. Engage with Dr. Starmer at DataHack Summit to explore the future of data analytics in a transformative way.

Right now, people all over the world are going bonkers over something called ChatGPT. In this workshop, we’ll learn the basic concepts behind how ChatGPT works and then learn how to code, train, and use our own version of it from scratch using PyTorch. From this coding experience, we’ll learn about the strengths and weaknesses of models like ChatGPT, as well as discuss alternative design strategies. Then we’ll learn how to fine-tune a production language model on a custom dataset. Fine-tuning on a custom dataset gives us more control over how the model behaves and can make it more reliable.

NOTE: This workshop will be done in “StatQuest Style” meaning every little detail will be clearly explained. We’ll also start each module with a silly song.

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Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More

Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More

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