Towards AI

SEPTEMBER 10, 2023

Detecting drought in January 2020 (on the left) using the EVI vegetation index Yellow means very healthy vegetation while dark green means unhealthy. Clustering similar fields using unsupervised K-means clustering The outcome of K-means clustering is cluster labels that assign each data point to one of the K clusters.

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Clustering Algorithm AI AI 122

AWS Machine Learning Blog

DECEMBER 22, 2023

As a result, machine learning practitioners must spend weeks of preparation to scale their LLM workloads to large clusters of GPUs. Aligning SMP with open source PyTorch Since its launch in 2020, SMP has enabled high-performance, large-scale training on SageMaker compute instances. To mitigate this problem, SMP v2.0

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Clustering Deep Learning Deep Learning AWS 126

AWS Machine Learning Blog

JUNE 7, 2023

Starting June 7th, both Falcon LLMs will also be available in Amazon SageMaker JumpStart, SageMaker’s machine learning (ML) hub that offers pre-trained models, built-in algorithms, and pre-built solution templates to help you quickly get started with ML. The model weights are available to download, inspect and deploy anywhere.

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Clustering Machine Learning Machine Learning AWS 102

IBM Data Science in Practice

JANUARY 4, 2023

Temperature observation at 1pm UTC on June 15, 2020 Wind speed observation at 1pm UTC on June 15, 2020 Data usage Most of our clients use weather data as a variable in their linear regression model and other machine learning models. June 2020 is ~540 GB). write.mode(params["mode"]).format(params["output"]).save(params["dest"])

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Analytics Analytics Python Clustering 130

Applied Data Science

AUGUST 2, 2021

Machine learning The 6 key trends you need to know in 2021 ? They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. Download the free, unabridged version here.

Data Science 130

Data Science Data Scientist ML ML 130

Flipboard

APRIL 4, 2023

The standard cells are then collected into clusters to help speed up the training process. Recall that, as a preprocessing step, the reinforcement learning method gathers up the standard cells into clusters. The macro-placing reinforcement learning portion has no knowledge of the initial placement, they say.

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EDA Algorithm Clustering Machine Learning 177

DataRobot

DECEMBER 20, 2021

Image recognition is one of the most relevant areas of machine learning. Deep learning makes the process efficient. In 2020, our team launched DataRobot Visual AI. We embedded best practices and various deep learning models to support image data. Multimodal Clustering. DataRobot Visual AI.

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Clustering Deep Learning Deep Learning Exploratory Data Analysis 97

Mlearning.ai

AUGUST 11, 2023

Authors of AntMan [1] propose a deep learning infrastructure, which is a co-design of cluster schedulers (e.g., with deep learning frameworks (e.g., Their motivation for this work was their observation on very low GPU utilization on Alibaba cluster. AntMan: Dynamic scaling on GPU clusters for deep learning.

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Deep Learning Deep Learning Clustering AI 52

Hacker News

NOVEMBER 15, 2023

The Story of the Name Patrick Lewis, lead author of the 2020 paper that coined the term , apologized for the unflattering acronym that now describes a growing family of methods across hundreds of papers and dozens of commercial services he believes represent the future of generative AI.

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Database AI AI Natural Language Processing 181

AWS Machine Learning Blog

OCTOBER 30, 2024

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval.

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Machine Learning Machine Learning AWS Data Scientist 110

AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. Journal of machine learning research 9, no.

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ML ML Machine Learning Machine Learning 98

Mlearning.ai

APRIL 8, 2023

SOTA (state-of-the-art) in machine learning refers to the best performance achieved by a model or system on a given benchmark dataset or task at a specific point in time. The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. 2020) “GPT-4 Technical report ” by Open AI.

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Natural Language Processing Algorithm Machine Learning Machine Learning 98

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. 2020): e0235424. Plos one 15.7

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AWS Analytics Analytics Machine Learning 101

Flipboard

MAY 29, 2025

Custom geospatial machine learning : Fine-tune a specialized regression, classification, or segmentation model for geospatial machine learning (ML) tasks. Points clustered closely on the y-axis indicate similar ground conditions; sudden and persistent discontinuities in the embedding values signal significant change.

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AWS ML ML Machine Learning 116

IBM Journey to AI blog

SEPTEMBER 13, 2023

Today, entire industries are looking to leverage the availability of complex space technologies and insights — from reusable rocket launchers to the use of open-source machine learning pipelines — to accelerate a new era of commercial space applications.

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AI AI Clustering Cloud Data 109

AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. in 2020 as a model where parametric memory is a pre-trained seq2seq model and the non-parametric memory is a dense vector index of Wikipedia, accessed with a pre-trained neural retriever. RAG models were introduced by Lewis et al.

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Algorithm Machine Learning Machine Learning Natural Language Processing 102

Dataconomy

APRIL 26, 2023

The strategic value of IoT development and data analytics Sierra Wireless Sierra Wireless , a wireless communications equipment designer and service provider, has been honing its focus on IoT software and managed services following its acquisition of M2M Group, a cluster of companies dedicated to IoT connectivity, in 2020.

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Internet of Things Azure AWS Cloud Computing 156

phData

NOVEMBER 9, 2023

The Snowflake Data Cloud was unveiled in 2020 as the next iteration of Snowflake’s journey to simplify how organizations interact with their data. What is the Snowflake Data Cloud? The Data Cloud applies technology to solve data problems that exist with every customer, namely; availability, performance, and access.

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Data Warehouse Data Lakes Clustering Cloud Data 98

AWS Machine Learning Blog

MAY 23, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of virtually infinite compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are rapidly adopting and using ML technologies to transform their businesses.

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AWS Machine Learning Blog

MAY 25, 2023

in 2020 as a model where parametric memory is a pre-trained seq2seq model and the non-parametric memory is a dense vector index of Wikipedia, accessed with a pre-trained neural retriever. He focuses on developing scalable machine learning algorithms. RAG models were introduced by Lewis et al.

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AWS Clustering Python ML 98

AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). Learning means identifying and capturing historical patterns from the data, and inference means mapping a current value to the historical pattern.

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AWS ML ML Clustering 117

Defined.ai blog

OCTOBER 9, 2022

Fight sophisticated cyber attacks with AI and ML When “virtual” became the standard medium in early 2020 for business communications from board meetings to office happy hours, companies like Zoom found themselves hot in demand. A basic example of an application of machine learning in cybersecurity is the spam filter in email inboxes.

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Artificial Intelligence Artificial Intelligence ML ML 52

ODSC - Open Data Science

MAY 30, 2023

For example, rising interest rates and falling equities already in 2013 and again in 2020 and 2022 led to drawdowns of risk parity schemes. His interests are financial markets, asset management, and machine learning applications.

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ML ML Data Science Machine Learning 52

AWS Machine Learning Blog

APRIL 19, 2024

This solution includes the following components: Amazon Titan Text Embeddings is a text embeddings model that converts natural language text, including single words, phrases, or even large documents, into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity.

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AWS ML ML Database 129

ODSC - Open Data Science

FEBRUARY 20, 2025

The model is trained on gameplay data from Bleeding Edge, a 2020 multiplayer game developed by NinjaTheory. Development The development of Muse was driven by advances in machine learning and the need to scale model training. The release marks a significant step toward integrating generative AI into game design.

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AI AI Azure Clustering 52

Tableau

DECEMBER 1, 2021

Even modern machine learning applications should use visual encoding to explain data to people. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. Gestalt properties including clusters are salient on scatters. Let’s take a look at each. . Query innovation.

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Tableau ML ML Database 145

Flipboard

NOVEMBER 24, 2023

Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. Since joining SnapLogic in 2010, Greg has helped design and implement several key platform features including cluster processing, big data processing, the cloud architecture, and machine learning.

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Database AWS ETL SQL 158

AWS Machine Learning Blog

NOVEMBER 22, 2023

For decades, Amazon has pioneered and innovated machine learning (ML), bringing delightful experiences to its customers. Similar to the rest of the industry, the advancements of accelerated hardware have allowed Amazon teams to pursue model architectures using neural networks and deep learning (DL). You can find him on LinkedIn.

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AWS ML ML Deep Learning 117

PyImageSearch

MAY 12, 2025

If you havent installed it yet, follow this step-by-step guide: Getting Started with Docker for Machine Learning. e "discovery.type=single-node" : Runs OpenSearch as a single-node cluster (since were not setting up a distributed system locally). pandas==2.0.3 tqdm==4.66.1 pyarrow==14.0.2

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AWS K-nearest Neighbors Deep Learning Deep Learning 73

AWS Machine Learning Blog

JULY 31, 2023

Machine learning (ML) methods can help identify suitable compounds at each stage in the drug discovery process, resulting in more streamlined drug prioritization and testing, saving billions in drug development costs (for more information, refer to AI in biopharma research: A time to focus and scale ).

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ML ML Database Algorithm 98

AWS Machine Learning Blog

APRIL 3, 2023

JumpStart is the machine learning (ML) hub of Amazon SageMaker that offers a one-click access to over 350 built-in algorithms; pre-trained models from TensorFlow, PyTorch, Hugging Face, and MXNet; and pre-built solution templates. He focuses on developing scalable machine learning algorithms.

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Natural Language Processing Machine Learning Machine Learning Algorithm 102

Mlearning.ai

JANUARY 31, 2023

Machine learning is a popular choice here. I tried several other machine learning classifiers, but SVM turned out to be the best. Furthermore, it involves just dot-products, a fast operation for nowadays machines to carry on. Of course, any machine learning algorithm requires a proper dataset to train on.

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Clustering Algorithm Machine Learning Machine Learning 52

The MLOps Blog

DECEMBER 28, 2022

Building ML team Following the surge in ML use cases that have the potential to transform business, the leaders are making a significant investment in ML collaboration, building teams that can deliver the promise of machine learning. Machine learning collaboration Gigaforce allocates work based on the phase of the project.

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ML ML Data Scientist Machine Learning 78

Pickl AI

JULY 18, 2023

AI Engineers focus primarily on implementing and deploying AI models and algorithms, working closely with data scientists and machine learning experts. Model Selection and Optimization Identifying appropriate machine learning models and techniques, fine-tuning parameters, and optimizing the performance of AI systems.

AI 52

AI AI Machine Learning Machine Learning 52

Tableau

DECEMBER 1, 2021

Even modern machine learning applications should use visual encoding to explain data to people. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. Gestalt properties including clusters are salient on scatters. Let’s take a look at each. . Query innovation.

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Tableau ML ML Database 98

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022.

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SQL ML ML Python 52