Pickl AI

JANUARY 23, 2023

It is mainly used for deep learning applications. PyTorch PyTorch is a popular, open-source, and lightweight machine learning and deep learning framework built on the Lua-based scientific computing framework for machine learning and deep learning algorithms. It also allows distributed training.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

ML 101

ML ML AWS Data Pipeline 101

AWS Machine Learning Blog

OCTOBER 23, 2024

At its core, Amazon Bedrock provides the foundational infrastructure for robust performance, security, and scalability for deploying machine learning (ML) models. The serverless infrastructure of Amazon Bedrock manages the execution of ML models, resulting in a scalable and reliable application.

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AI AI Database AWS 84

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 68

Data Science Machine Learning Machine Learning ML 68

The MLOps Blog

NOVEMBER 30, 2022

These days enterprises are sitting on a pool of data and increasingly employing machine learning and deep learning algorithms to forecast sales, predict customer churn and fraud detection, etc., ML model versioning: where are we at? across industries and domains.

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ML ML Machine Learning Machine Learning 52

Towards AI

FEBRUARY 27, 2024

Looking ahead, it has served the ML community a lot while building different Natural Language Understanding tools and models as a high-quality curated corpus of information. The open-source movement gained hold with the rise of the Internet, and it has since grown into a vibrant scene with many contributors and projects.

Machine Learning 111

Machine Learning Machine Learning Deep Learning Deep Learning 111

Towards AI

APRIL 19, 2024

Intelligent Medical Objects 👉Industry domain: AI, Health Tech, IT, NLP, Software, Analytics, Generative AI 👉Location: 3 offices 👉Year founded: 1994 👉Programming languages deployed: Angular, C#, SQL, Scikit, TensorFlow, Spark, GitHub, R, Python 👉Benefits: Flexible time off, family medical leave, pet insurance, (..)

AI 109

AI AI Artificial Intelligence Artificial Intelligence 109

AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. It involves training a global machine learning (ML) model from distributed health data held locally at different sites. Import the data loader into the training script.

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AWS Analytics Analytics Machine Learning 94

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2015; Huang et al., an image) with the intention of causing a machine learning model to misclassify it (Goodfellow et al., 2012; Otsu, 1979; Long et al.,

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Mlearning.ai

JUNE 16, 2023

The common practice for developing deep learning models for image-related tasks leveraged the “transfer learning” approach with ImageNet. ML practitioners, believing they had to match the sheer size of ImageNet, refrained from pre-training with much smaller available medical image datasets, let alone developing new ones.

AI 52

AI AI ML ML 52

AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 89

ML ML Deep Learning Deep Learning 89

ML Review

FEBRUARY 26, 2018

Launched in July 2015, AliMe is an IHCI-based shopping guide and assistant for e-commerce that overhauls traditional services, and improves the online user experience. Chitchatting, such as “I’m in a bad mood”, pulls up a method that marries the retrieval model with deep learning (DL). 5] Mnih V, Badia A P, Mirza M, et al.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

JULY 24, 2023

This article will cover briefly the architecture of the deep learning model used for the purpose. Koltun, “Multi-scale context aggregation by dilated convolutions,” arXiv preprint arXiv:1511.07122, 2015. [4] which was published on March 28, 2023. We pay our contributors, and we don’t sell ads.

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Deep Learning Deep Learning AI AI 52

ML Review

MARCH 31, 2019

Source: Explaining and Harnessing Adversarial Examples , Goodfellow et al, ICLR 2015. Source: Robust Physical-World Attacks on Deep Learning Visual Classification. Source: Explaining and Harnessing Adversarial Examples , Goodfellow et al, ICLR 2015. Robust Physical-World Attacks on Deep Learning Visual Classification.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress.

Machine Learning 52

Machine Learning Machine Learning Computer Science Computer Science 52

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress.

Machine Learning 52

Machine Learning Machine Learning Computer Science Computer Science 52

Iguazio

MARCH 1, 2024

The manufacturing industry can benefit from AI, data and machine learning to advance manufacturing quality and productivity, minimize waste and reduce costs. With ML, manufacturers can modernize their businesses through use cases like forecasting demand, optimizing scheduling, preventing malfunctioning and managing quality.

ML 52

ML ML Machine Learning Machine Learning 52

PyImageSearch

JULY 3, 2023

Figure 4: The Netflix personalized home page generation problem (source: Alvino and Basilico, “Learning a Personalized Homepage,” Netflix Technology Blog , 2015 ). Machine Learning for Page Generation A good utility function that checks the relevance of a row is the core of building a personalized home page.

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

ML Review

JUNE 4, 2018

However, in 2014 a number of high-profile AI labs began to release new approaches leveraging deep learning to improve performance. An example of such an approach is seen in the work of Karpathy and Fei-Fei (2015)[ 78 ]. Largely due to the limits of heuristics or approximations for word-object relationships[ 52 ][ 53 ][ 54 ].

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Heartbeat

DECEMBER 20, 2023

Understanding why ResNet is essential, its innovative aspects, and what it enables in deep learning forms a crucial part of our exploration. This comparison is academic and practical, offering deep learning practitioners insights into choosing the right architecture based on specific project needs.

Deep Learning 52

Deep Learning Deep Learning Data Science Machine Learning 52

ML Review

MAY 3, 2018

Much the same way we iterate, link and update concepts through whatever modality of input our brain takes — multi-modal approaches in deep learning are coming to the fore. While an oversimplification, the generalisability of current deep learning approaches is impressive.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52

Mlearning.ai

JUNE 5, 2023

Many Libraries: Python has many libraries and frameworks (We will be looking some of them below) that provide ready-made solutions for common computer vision tasks, such as image processing, face detection, object recognition, and deep learning. TensorFlow An open-source framework for machine learning and deep learning.

Deep Learning 52

Deep Learning Deep Learning Python Machine Learning 52

Heartbeat

APRIL 23, 2023

SpaCy is a popular open-source NLP library developed in 2015 by Matthew Honnibal and Ines Montani, the founders of the software company Explosion. Editorially independent, Heartbeat is sponsored and published by Comet, an MLOps platform that enables data scientists & ML teams to track, compare, explain, & optimize their experiments.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning Deep Learning 52

Heartbeat

AUGUST 21, 2023

AlexNet significantly improved performance over previous approaches and helped popularize deep learning and CNNs. ResNet is a deep CNN architecture developed by Kaiming He and his colleagues at Microsoft Research in 2015. It consists of 16 layers, all of which are convolutional or fully connected layers.

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning ML 52

AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 52

ML ML Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. Active learning is a really powerful data selection technique for reducing labeling costs.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. Active learning is a really powerful data selection technique for reducing labeling costs.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. Active learning is a really powerful data selection technique for reducing labeling costs.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

FEBRUARY 13, 2023

In addition, we are also responsible for the Experimentation Platforms at Comcast and the products, the data platforms that kind of underlie all these AI and machine-learning applications, as well as our product analytics platforms that make it easier to train, develop, and manage models. The voice remote was launched for Comcast in 2015.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Snorkel AI

FEBRUARY 13, 2023

In addition, we are also responsible for the Experimentation Platforms at Comcast and the products, the data platforms that kind of underlie all these AI and machine-learning applications, as well as our product analytics platforms that make it easier to train, develop, and manage models. The voice remote was launched for Comcast in 2015.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

DrivenData Labs

SEPTEMBER 10, 2024

Many teams combined technical skills in AI/ML with domain knowledge in neuroscience, aging, or healthcare. Paola Ruíz Puente is a Biomedical Engineer amd the AI/ML manager at IGC Pharma. Pablo Arbeláez is a distinguished researcher with over 20 years of experience using AI/ML in medicine, biology, and computer vision.

Machine Learning 147

Machine Learning Machine Learning Computer Science Computer Science 147

Dataconomy

MARCH 19, 2025

Tensor Processing Units (TPUs) represent a significant leap in hardware specifically designed for machine learning tasks. They are essential for processing large amounts of data efficiently, particularly in deep learning applications. For flexible models and less intensive tasks, CPUs still hold significant utility.

Machine Learning 91

Machine Learning Machine Learning Natural Language Processing Deep Learning 91