PyImageSearch

JULY 3, 2023

In this blog post, we will dive deeper into the Netflix movies and series recommendation systems ( Figure 1 ). And, thanks to Netflix recommendations, we don’t have to worry about what to watch. This data includes your location, watch history, ratings, device information, whether you left the show in the middle, etc.

Computer Vision 52

Computer Vision Deep Learning Algorithm Machine Learning 52

Google Research AI blog

JANUARY 24, 2023

In this blogpost, we share ways we have approached Responsible AI across our research in the past year and where we’re headed in 2023. In computer vision, we studied the robustness of new vision transformer models and developed new negative data augmentation techniques to improve their robustness.

Responsible AI 99

Responsible AI AI AI ML 99

deepsense.ai

NOVEMBER 30, 2023

In this blog post, we will focus on the widely-discussed Llama 2 model. What is Llama 2, and why is there so much buzz around it? What is Llama 2, and why is there so much buzz around it? We will go through the technicalities, safety issues, the tools built around it, and the possibilities of using the model.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

PyImageSearch

AUGUST 14, 2023

Selection Bias and Cold Start Along with capturing the asymmetry in the co-purchase relationship, related-product recommendations suffer from the challenge of selection bias, which is inherent to historical purchase data due to product availability, price, etc. This lesson will cover several aspects of Amazon recommendations (e.g.,

Computer Vision 98

Computer Vision Deep Learning Algorithm Neural Network 98

Snorkel AI

MARCH 1, 2023

What are they and how will they impact your business? Table of contents What are foundation models? Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Find out in the guide below. I left it here yesterday.”

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BERT Natural Language Processing Large Language Models Neural Network 83

AWS Machine Learning Blog

MAY 22, 2023

The power of LLMs comes from their capacity to learn and generalize from extensive and diverse training data. Text completion or imputation is one of the most common unsupervised objectives: given a chunk of text, the model learns to accurately predict what comes next (for example, predict the next sentence). 2] to fine-tune the model.

Natural Language Processing 85

Natural Language Processing Machine Learning Computational Linguistics NLP 85

PyImageSearch

MAY 29, 2023

Furthermore, we look closer at the Apples2Oranges Dataset and discuss dataset preprocessing techniques, allowing us to process our input data and build our end-to-end image translation model. Notice that the dataset consists of approximately equal numbers of apple and orange data samples. The inference.py

Computer Vision 56

Computer Vision Deep Learning Artificial Intelligence Artificial Intelligence 56

Heartbeat

FEBRUARY 2, 2024

The challenges presented by this dataset contribute to advancements in the intersection of computer vision and natural language understanding, pushing the boundaries of what models can achieve regarding visual comprehension and reasoning. or Visual Question Answering version 2.0, An extension of its predecessor, VQA v2.0

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

PyImageSearch

SEPTEMBER 11, 2023

Jump Right To The Downloads Section SAM from Meta AI (Part 1): Segmentation with Prompts In the past, computer vision models have mostly relied on methods trained on a specific task with task-specific annotated datasets. They can perform that particular task on novel examples at test time. without further fine-tuning).

Computer Vision 117

Computer Vision AI AI Prompt Engineer 117

PyImageSearch

APRIL 3, 2023

Jump Right To The Downloads Section Deploying a Custom Image Classifier on an OAK-D Introduction As a deep learning engineer or practitioner, you may be working in a team building a product that requires you to train deep learning models on a specific data modality (e.g., computer vision) on a daily basis.

Neural Network 64

Neural Network Computer Vision Deep Learning Artificial Intelligence 64

Topbots

APRIL 28, 2023

Generated by the author This article was originally published on the author’s blog and re-published to TOPBOTS with permission from the author. GPT-4 (2023, ~100T parameters). But is it possible to measure the level of creative process more broadly in these models? While there are multiple versions of GPT-3.5, I used gpt-3.5-turbo

Large Language Models 52

Large Language Models Natural Language Processing Robotics Explainability 52