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In this Deep Learning Institute (DLI) workshop, participants will learn the fundamentals of multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software. This course will build intuition and experience in Python with the PyTorch library and many topics related to Deep Learning.
By participating in this workshop, you’ll:
- Learn the fundamental techniques and tools required to train a deep learning model
- Gain experience with common deep learning data types and model architectures
- Enhance datasets through data augmentation to improve model accuracy
- Leverage transfer learning between models to achieve efficient results with less data
and computation - Build confidence to take on your own project with a modern deep learning framework
Topics: PyTorch, Pandas, Convolutional Neural Networks (CNNs), Data Augmentation, Transfer Learning, Natural Language Processing
Prerequisites: Experience with Python, functions, loops, dictionaries, and arrays. Pandas Data Processing, Computing Regression lines.
Assessment Type: Code-based
Certificate available