Unite.AI

AUGUST 29, 2023

In the past few years, Artificial Intelligence (AI) and Machine Learning (ML) have witnessed a meteoric rise in popularity and applications, not only in the industry but also in academia. Recent research in the field of IoT edge computing has demonstrated the potential to implement Machine Learning techniques in several IoT use cases.

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Pickl AI

JANUARY 23, 2023

Introduction to Machine Learning Frameworks In the present world, almost every organization is making use of machine learning and artificial intelligence in order to stay ahead of the competition. So, let us see the most popular and best machine learning frameworks and their uses.

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The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. Pay-as-you-go pricing makes it easy to scale when needed.

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Unite.AI

JUNE 24, 2024

Machine Learning Operations (MLOps) is a set of practices and principles that aim to unify the processes of developing, deploying, and maintaining machine learning models in production environments. Types of MLOps Tools MLOps tools play a pivotal role in every stage of the machine learning lifecycle.

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Dlabs.ai

JUNE 11, 2019

How to use deep learning (even if you lack the data)? You can create synthetic data that acts just like real data – and so allows you to train a deep learning algorithm to solve your business problem, leaving your sensitive data with its sense of privacy, intact. What is deep learning?

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Flipboard

JUNE 26, 2023

These techniques utilize various machine learning (ML) based approaches. Overview of solution In this post, we go through the various steps to apply ML-based fuzzy matching to harmonize customer data across two different datasets for auto and property insurance. The following diagram shows our solution architecture.

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Mlearning.ai

MAY 8, 2023

About this series In this series , we will learn how to code the must-to-know deep learning algorithms such as convolutions, backpropagation, activation functions, optimizers, deep neural networks, and so on using only plain and modern C++. A hamster? A Guinea Pig? exp(); Vector sums = expo.colwise().sum();

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Becoming Human

MARCH 16, 2023

Photo by NASA on Unsplash Hello and welcome to this post, in which I will study a relatively new field in deep learning involving graphs — a very important and widely used data structure. This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Background of multimodality models Machine learning (ML) models have achieved significant advancements in fields like natural language processing (NLP) and computer vision, where models can exhibit human-like performance in analyzing and generating content from a single source of data. Outside of work, he enjoys reading and traveling.

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AWS Machine Learning Blog

APRIL 8, 2024

of Large Model Inference (LMI) Deep Learning Containers (DLCs). We set this value to max (maximum GPU on the current machine). For the TensorRT-LLM container, we use auto. Similarly, you can use log_prob as measure of confidence score for classification use cases.

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ODSC - Open Data Science

APRIL 17, 2023

Low-Code PyCaret: Let’s start off with a low-code open-source machine learning library in Python. PyCaret allows data professionals to build and deploy machine learning models easily and efficiently. Well, one of its main advantages is that PyCaret reduces the amount of code required to build a machine learning model.

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AWS Machine Learning Blog

MAY 31, 2024

The Falcon 2 11B model is available on SageMaker JumpStart, a machine learning (ML) hub that provides access to built-in algorithms, FMs, and pre-built ML solutions that you can deploy quickly and get started with ML faster. It’s built on causal decoder-only architecture, making it powerful for auto-regressive tasks.

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Heartbeat

JUNE 27, 2023

They are as follows: Node-level tasks refer to tasks that concentrate on nodes, such as node classification, node regression, and node clustering. Edge-level tasks , on the other hand, entail edge classification and link prediction. Graph-level tasks involve graph classification, graph regression, and graph matching.

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Marktechpost

OCTOBER 8, 2023

By providing object instance-level classification and semantic labeling, 3D semantic instance segmentation tries to identify items in a given 3D scene represented by a point cloud or mesh. They use an auto-labeling approach to distinguish between known and unknowable class labels to produce pseudo-labels during training.

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AWS Machine Learning Blog

JUNE 12, 2023

It can support a wide variety of use cases, including text classification, token classification, text generation, question and answering, entity extraction, summarization, sentiment analysis, and many more. It uses attention as the learning mechanism to achieve close to human-level performance. 24xlarge, ml.g5.48xlarge, ml.p4d.24xlarge,

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Unite.AI

DECEMBER 19, 2023

Carl Froggett, is the Chief Information Officer (CIO) of Deep Instinct , an enterprise founded on a simple premise: that deep learning , an advanced subset of AI, could be applied to cybersecurity to prevent more threats, faster. But not all AI is created equal. This makes it extremely fast and privacy-friendly.

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AWS Machine Learning Blog

MAY 31, 2023

PyTorch is a machine learning (ML) framework based on the Torch library, used for applications such as computer vision and natural language processing. For a list of NVIDIA Triton Deep Learning Containers (DLCs) supported by SageMaker inference, refer to Available Deep Learning Containers Images.

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AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. The architecture of DJL is engine agnostic.

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Heartbeat

DECEMBER 27, 2023

Photo by Ian Taylor on Unsplash This article will comprehensively create, deploy, and execute machine learning application containers using the Docker tool. It will further explain the various containerization terms and the importance of this technology to the machine learning workflow. Yes, they do, but partially.

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AWS Machine Learning Blog

MAY 2, 2023

With the ability to solve various problems such as classification and regression, XGBoost has become a popular option that also falls into the category of tree-based models. In this post, we dive deep to see how Amazon SageMaker can serve these models using NVIDIA Triton Inference Server.

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AWS Machine Learning Blog

MARCH 1, 2023

Statistical methods and machine learning (ML) methods are actively developed and adopted to maximize the LTV. In this post, we share how Kakao Games and the Amazon Machine Learning Solutions Lab teamed up to build a scalable and reliable LTV prediction solution by using AWS data and ML services such as AWS Glue and Amazon SageMaker.

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Marktechpost

DECEMBER 16, 2023

The X-Raydar achieved a mean AUC of 0.919 on the auto-labeled set, 0.864 on the consensus set, and 0.842 on the MIMIC-CXR test. For testing, a consensus set of 1,427 images annotated by expert radiologists, an auto-labeled set (n=103,328), and an independent dataset, MIMIC-CXR (n=252,374), were employed.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

Thomson Reuters , a global content and technology-driven company, has been using artificial intelligence and machine learning (AI/ML) in its professional information products for decades. It provides resilient and persistent clusters for large-scale deep learning training of FMs on long-running compute clusters.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Amazon Elastic Compute Cloud (Amazon EC2) DL2q instances, powered by Qualcomm AI 100 Standard accelerators, can be used to cost-efficiently deploy deep learning (DL) workloads in the cloud. This is a guest post by A.K Roy from Qualcomm AI. The cores are interconnected with a high-bandwidth low-latency network-on-chip (NoC) mesh.

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Mlearning.ai

JUNE 22, 2023

Understanding the biggest neural network in Deep Learning Join 34K+ People and get the most important ideas in AI and Machine Learning delivered to your inbox for free here Deep learning with transformers has revolutionized the field of machine learning, offering various models with distinct features and capabilities.

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Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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Heartbeat

JUNE 26, 2023

Today, I’ll walk you through how to implement an end-to-end image classification project with Lightning , Comet ML, and Gradio libraries. First, we’ll build a deep-learning model with Lightning. PyTorch-Lightning As you know, PyTorch is a popular framework for building deep learning models.

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AWS Machine Learning Blog

JANUARY 10, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. This model can perform a number of tasks, but we send a payload specifically for sentiment analysis and text classification. Auto scaling. Depending on your traffic patterns, you can attach an auto scaling policy to your SageMaker endpoint.

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Marktechpost

JULY 24, 2023

Machine learning has increased considerably in several areas due to its performance in recent years. Thanks to modern computers’ computing capacity and graphics cards, deep learning has made it possible to achieve results that sometimes exceed those experts give.

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Towards AI

JULY 23, 2023

The architecture is an auto-regressive architecture, i.e., the model produces one word at a time and then takes in the sequence attached with the predicted word, to predict the next word. Basically, it predicts a word with the context of the previous word.

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AWS Machine Learning Blog

MARCH 2, 2023

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. eks-create.sh This will create one instance of each type.

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Heartbeat

JULY 17, 2023

Comet, a cloud-based machine learning platform, offers a powerful solution for tracking, comparing, and benchmarking fine-tuned models, allowing users to easily analyze and visualize their performance. However, the lessons you’ll learn from this tutorial will help you benchmark more computer vision models.

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The MLOps Blog

MARCH 23, 2023

These models have achieved various groundbreaking results in many NLP tasks like question-answering, summarization, language translation, classification, paraphrasing, et cetera. Likewise, according to AWS , inference accounts for 90% of machine learning demand in the cloud. 2020 or Hoffman et al.,

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Heartbeat

MARCH 1, 2023

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. A convolutional neural network (CNN) is primarily used for image classification.

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Marktechpost

MARCH 6, 2025

Transformers provides pre-built NLP models, torch serves as the backend for deep learning tasks, and accelerate ensures efficient resource utilization on GPUs. This compact, instruction-tuned model is optimized to handle tasks like sentiment classification directly within Colab, even under limited computational resources.

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AWS Machine Learning Blog

MARCH 1, 2023

Machine learning (ML) engineers can fine-tune and deploy text-to-semantic-segmentation and in-painting models based on pre-trained CLIPSeq and Stable Diffusion with Amazon SageMaker. Hugging Face and Amazon introduced Hugging Face Deep Learning Containers (DLCs) to scale fine tuning tasks across multiple GPUs and nodes.

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Viso.ai

MARCH 29, 2024

About us: At viso.ai, we’ve built the end-to-end machine learning infrastructure for enterprises to scale their computer vision applications easily. Streamlit is a Python-based library specifically developed for machine learning engineers. Computer vision and machine learning specialists are not web developers.

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