Name: Intro to Deep Learning
Start: 2025-12-24T18:00:00-06:00
End: 2025-12-24T20:00:00-06:00
Location: Walker Library

Intro to Deep Learning (Using Deep Learning with Python, 3rd Ed.)

Curious about deep learning but don’t know where to start? Join our in-person, hands-on meetup at the library as we work through François Chollet’s brand-new Deep Learning with Python, Third Edition. We’ll demystify neural nets from first principles and build real models together using Python. The book is a complete, modern rewrite that now covers Keras 3, TensorFlow, PyTorch, JAX, and today’s generative AI techniques—all taught by the creator of Keras. ￼

What we’ll cover (highlights from the new 3rd edition)
• Foundations: core deep learning ideas and a code-first, intuitive approach. ￼
• Modern tooling: Keras 3 across multiple backends, with primers on TensorFlow, PyTorch, and JAX. ￼
• Computer vision: image classification, image segmentation, and an intro to object detection. ￼
• Timeseries: practical forecasting workflows. ￼
• NLP & LLMs: text classification, machine translation, and large language models—including building a small GPT-like model and understanding sampling/decoding. ￼
• Generative images: diffusion-based image generation (the tech behind modern AI art tools). ￼
• Scaling & tuning: tips for faster training, multi-GPU/TPU, and model optimization. ￼
• Bigger & better than before: the third edition adds \~30% more content and reflects the 2024–2025 state of the art. ￼

Who it’s for
• Python-comfortable beginners to ML (you don’t need prior machine learning or heavy math). ￼

How we’ll learn
• Short explanations + live coding in Python each session.
• We’ll follow the book’s examples (with cross-references to PyTorch/JAX where helpful).
• Optional: run the official companion notebooks from the authors’ GitHub. ￼

Getting the book
• You can read the 3rd edition online for free on the official site, with runnable code links in each chapter. https://deeplearningwithpython.io/
• Release details: Manning lists the print/ePub/liveBook availability as September 30, 2025; Amazon lists the Kindle edition publication date as October 14, 2025. ￼

What to bring
• Laptop with Python 3 and a Jupyter environment. We’ll start with Keras 3 + TensorFlow; PyTorch/JAX are welcome too. (We’ll share an environment setup link at the start.) ￼

Location & vibe
• Where: [Library Meeting Room], with tables, power, and Wi-Fi.
• Format: 15-minute mini-lecture → 60-minute guided coding → 15-minute Q&A/show-and-tell.
• Experience level: friendly to newcomers; helpful for practitioners who want a 2025 refresh.

RSVP to save your seat—bring your curiosity and a laptop. Let’s learn by building!

Discord server: https://discord.gg/4YpvXGcggj

Yaniv

Twin Cities Deep Learning Study Group

Technology

Artificial Intelligence

Deep Learning

Data Science

Machine Intelligence

Artificial Intelligence Applications

Neural Networks

Predictive Analytics

Data Analytics

Machine Learning

Natural Language Processing

Big Data

Python

Data Science using Python

Every week on Wednesday until March 20, 2026

Intro to Deep Learning

Walker Library

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Twin Cities Deep Learning Study Group

Intro to Deep Learning

Twin Cities Deep Learning Study Group

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