AWS Machine Learning Blog

SEPTEMBER 18, 2024

Zeta’s AI innovations over the past few years span 30 pending and issued patents, primarily related to the application of deep learning and generative AI to marketing technology. It simplifies feature access for model training and inference, significantly reducing the time and complexity involved in managing data pipelines.

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Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

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Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Dataconomy

MARCH 27, 2023

Limitations: Bias and interpretability:  Machine learning algorithms may reflect biases present in the data used to train them, and it may be challenging to interpret how they arrived at their decisions. On the other hand, ML requires a significant amount of data preparation and model training before it can be deployed.

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Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

Improve the quality and time to market for deep learning models in diagnostic medical imaging. Data Management – Efficient data management is crucial for AI/ML platforms. Regulations in the healthcare industry call for especially rigorous data governance.

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Pickl AI

NOVEMBER 28, 2024

For example, in neural networks, data is represented as matrices, and operations like matrix multiplication transform inputs through layers, adjusting weights during training. Without linear algebra, understanding the mechanics of Deep Learning and optimisation would be nearly impossible.

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Pickl AI

NOVEMBER 18, 2024

Summary: The blog provides a comprehensive overview of Machine Learning Models, emphasising their significance in modern technology. It covers types of Machine Learning, key concepts, and essential steps for building effective models. Key Takeaways Machine Learning Models are vital for modern technology applications.

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Heartbeat

AUGUST 21, 2023

AlexNet significantly improved performance over previous approaches and helped popularize deep learning and CNNs. This helps avoid disappearing gradients in very deep networks, allowing ResNet to attain cutting-edge performance on a wide range of computer vision applications. We pay our contributors, and we don’t sell ads.

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Heartbeat

JANUARY 9, 2024

Proper data management enables optimal LLM capacitive performance in language-centric AI applications. MLOps requires a specialized approach to handle the unique characteristics of textual data and manage large datasets for pre-training and fine-tuning. We pay our contributors, and we don't sell ads.

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Mlearning.ai

NOVEMBER 29, 2023

Scientific studies forecasting  — Machine Learning and deep learning for time series forecasting accelerate the rates of polishing up and introducing scientific innovations dramatically. 19 Time Series Forecasting Machine Learning Methods How exactly does time series forecasting machine learning work in practice?

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Snorkel AI

AUGUST 22, 2023

We began by developing a suite of deep learning models trained on Wayfair imagery that can extract these product tags at scale. However, we have thousands of tags and building models for these tags requires a large amount of labeled data for training and highly curated ground truth data for evaluation.

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Machine Learning Machine Learning Data Preparation Data Scientist 52

Iguazio

FEBRUARY 8, 2024

LLM models are large deep learning models that are trained on vast datasets, are adaptable to various tasks and specialize in NLP tasks. They are characterized by their enormous size, complexity, and the vast amount of data they process. This includes versioning, ingestion and ensuring data quality.

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Snorkel AI

AUGUST 22, 2023

We began by developing a suite of deep learning models trained on Wayfair imagery that can extract these product tags at scale. However, we have thousands of tags and building models for these tags requires a large amount of labeled data for training and highly curated ground truth data for evaluation.

Machine Learning 52

Machine Learning Machine Learning Data Preparation Data Scientist 52

Snorkel AI

AUGUST 22, 2023

We began by developing a suite of deep learning models trained on Wayfair imagery that can extract these product tags at scale. However, we have thousands of tags and building models for these tags requires a large amount of labeled data for training and highly curated ground truth data for evaluation.

Machine Learning 52

Machine Learning Machine Learning Data Preparation Data Scientist 52