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Getting Started with Vector-Based Search
Editor’s note: Laura is a speaker for ODSC East 2022. Be sure to check out her talk, “Vector Database Workshop Using Weaviate,” to learn more about vector-based search! Traditional search engines perform a keyword-based search. Such search engines return results that contain an exact match or... Read more
Repo of the Week: Instant Neural Graphics Primitives
A team of researchers from NVIDIA including Thomas Muller, Alex Evans, Christoph Schied, and Alexander Keller,  demonstrated a new method that should enable the efficient use of artificial neural networks for rendering computer graphics.  Rendering is a notoriously slow process so this is a significant development... Read more
Higher-level PyTorch APIs: A short introduction to PyTorch Lightning 
In recent years, the PyTorch community developed several different libraries and APIs on top of PyTorch. PyTorch Lightning (Lightning for short) is one of them, and it makes training deep neural networks simpler by removing much of the boilerplate code. However, while Lightning’s focus lies in... Read more
Benchmarking a Computer Vision Deep Learning Pipeline with Distributed Computing
Editor’s Note: Jennifer is a speaker for ODSC East 2022. Be sure to check out her talk, “Creating a Benchmark for a Large-Scale Image Captioning Pipeline,” to learn more about computer vision deep learning there! Computer vision has an essential role in solving some of the... Read more
TensorFlow for Computer Vision – Transfer Learning Made Easy
Writing neural network model architectures from scratch involves a lot of guesswork. How many layers? How many nodes per layer? What activation function to use? Regularization? You won’t run out of questions any time soon. Transfer learning takes a different approach. Instead of starting from scratch,... Read more
Melting Pot and the Reverse-Engineering Approach to Multi-Agent Artificial General Intelligence
Editor’s Note: Joel is a speaker for ODSC East 2022. Be sure to check out his talk, “Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot,” there! Homo sapiens are a funny species. Along most of the traditionally studied domains of intelligence, we do not outshine... Read more
Recap of the First ODSC Ai+ Deep Learning Bootcamp Session
We recently finished our first session of Jon Krohn’s Deep Learning Bootcamp, and we’re already excited for part 2. Here are a few highlights from the session, some thoughts from attendees, and what to expect from part 2 and beyond. Session 1 Recap: How Deep Learning... Read more
Guidelines for Choosing an Optimizer and Loss Functions When Training Neural Networks
There’s no one right way to train a neural network. These models serve various functions with multiple data sets, so what produces a high-performing model in one instance may not in another. As a result, effective training relies on a series of tools and strategies. Two... Read more
The ODSC Warmup Guide to Keras
Keras is a Python library for deep learning. Deep learning is a sub-branch of artificial intelligence that focuses on solving complex computations by emulating the working process of a human brain. Neural networks, computational graphs composed of nodes representing multiple operators for breaking down the tasks... Read more
Google AI Proposes Temporal Fusion Transformer for Multi-Horizon Time Series Forecasting
Time series forecasting is a useful data science tool for helping people predict what will happen in the future based on historical, time-stamped information. Google researchers recently explained how they developed and used the company’s Temporal Fusion Transformer (TFT) to achieve more progress with these types... Read more