Mlearning.ai

FEBRUARY 27, 2023

Recently as I focused more on how to make proper data science projects that would be better fit for production, I started to pick up various tools and practices and figured out which were the best for me. However, for the intent of this article, I will strictly follow this principle as demonstrated by the book mentioned above.

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Iguazio

FEBRUARY 8, 2024

To read more about LLMOps and MLOps, checkout the O’Reilly book “Implementing MLOps in the Enterprise” , authored by Iguazio ’s CTO and co-founder Yaron Haviv and by Noah Gift. LLMOps (Large Language Model Operations), is a specialized domain within the broader field of machine learning operations (MLOps). What is LLMOps?

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Pickl AI

JULY 2, 2024

Sorting Algorithms Sorting algorithms play a crucial role in data preparation. Algorithms with low complexity for processing training data are crucial for faster model development and iteration cycles. Data Cleaning and Preprocessing Cleaning and preparing messy real-world data can be computationally expensive.

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PyImageSearch

NOVEMBER 6, 2023

This configuration ensures that our model is trained efficiently and effectively, leveraging the best practices in deep learning. The torch library is essential for our deep learning tasks, while the Dataset class from torch.utils.data provides a template for creating custom datasets ( Lines 7 and 9 ).

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Snorkel AI

MARCH 19, 2024

Google’s thought leadership in AI is exemplified by its groundbreaking advancements in native multimodal support (Gemini), natural language processing (BERT, PaLM), computer vision (ImageNet), and deep learning (TensorFlow). Book a demo today. See what Snorkel option is right for you.

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Snorkel AI

MARCH 19, 2024

Google’s thought leadership in AI is exemplified by its groundbreaking advancements in native multimodal support (Gemini), natural language processing (BERT, PaLM), computer vision (ImageNet), and deep learning (TensorFlow). See what Snorkel can do to accelerate your data science and machine learning teams.

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The MLOps Blog

FEBRUARY 22, 2024

Important note: Continual learning aims to allow the model to effectively learn new concepts while ensuring it does not forget already acquired information. Plenty of CL techniques exist that are useful in various machine-learning scenarios. There is no incremental training and no continual learning.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

You marked your calendars, you booked your hotel, and you even purchased the airfare. Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! Reserve your seat now!

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Thirdly, the presence of GPUs enabled the labeled data to be processed. Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. In order to train transformer models on internet-scale data, huge quantities of PBAs were needed.

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

In the following sections, we break down the data preparation, model experimentation, and model deployment steps in more detail. Data preparation Scalable Capital uses a CRM tool for managing and storing email data. She is responsible for data-driven approaches and use cases in the company together with her teams.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Databricks is getting up to 40% better price-performance with Trainium-based instances to train large-scale deep learning models. It can also connect to your internal intranet, wikis, and run books, and with the Amazon Q SDK, you can build a connection to whichever internal application you would like.

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PyImageSearch

NOVEMBER 18, 2024

We will start by setting up libraries and data preparation. Course information: 86 total classes • 115+ hours of on-demand code walkthrough videos • Last updated: October 2024 ★★★★★ 4.84 (128 Ratings) • 16,000+ Students Enrolled I strongly believe that if you had the right teacher you could master computer vision and deep learning.

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