KDnuggets

MARCH 13, 2020

After spending a lot of time thinking about the paths that software companies take toward ML maturity, this framework was created to follow as you adopt ML and then mature as an organization.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

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Machine Learning (Theory)

DECEMBER 1, 2020

This post is cross-listed on the CMU ML blog. The International Conference on Machine Learning (ICML) is a flagship machine learning conference that in 2020 received 4,990 submissions and managed a pool of 3,931 reviewers and area chairs. In this post, we summarize the results of these studies. Resubmission Bias Motivation.

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KDnuggets

MARCH 25, 2020

If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you. If your team has started using ?Ray? and you’re wondering what it is, this post is for you.

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KDnuggets

DECEMBER 16, 2019

It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.

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NYU Center for Data Science

SEPTEMBER 28, 2023

Building on this momentum is a dynamic research group at the heart of CDS called the Machine Learning and Language (ML²) group. By 2020, ML² was a thriving community, primarily known for its recurring speaker series where researchers presented their work to peers. What does it mean to work in NLP in the age of LLMs?

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KDnuggets

DECEMBER 11, 2019

We asked top experts: What were the main developments in AI, Data Science, Deep Learning, and Machine Learning Research in 2019, and what key trends do you expect in 2020? Read their answers, and also check 10 Free Top Notch Machine Learning Courses; 4 Hottest Trends in Data Science; The Essential Toolbox for Data Cleaning, and more.

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KDnuggets

DECEMBER 18, 2019

Build Pipelines with Pandas Using pdpipe; AI, Analytics, ML, DS, Technology Main Developments, Key Trends; New Poll: Does AutoML work? Ultralearn Data Science; Python Dictionary How-To; Top stories of 2019 and more.

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The MLOps Blog

DECEMBER 28, 2022

The onset of the pandemic has triggered a rapid increase in the demand and adoption of ML technology. 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.

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AWS Machine Learning Blog

NOVEMBER 29, 2024

For example, marketing and software as a service (SaaS) companies can personalize artificial intelligence and machine learning (AI/ML) applications using each of their customer’s images, art style, communication style, and documents to create campaigns and artifacts that represent them. year-over-year (13.8% on a GAAP basis, 57.9%

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Towards AI

NOVEMBER 16, 2024

Vishnoi, “A convergent and dimension-independent first-order algorithm for min-maxoptimization,” arXiv preprint arXiv:2006.12376, 2020.[2] 139–144, 2020.[3] 4880–4889, 2020.[9] 1153–1165, 2020.[15] Goodfellow, J. Pouget-Abadie, M. Warde-Farley, S. Courville, and Y. Arjovsky, S. Chintala, and L. 214–223, 2017.[4]

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IBM Data Science in Practice

MARCH 8, 2023

The growth of the AI and Machine Learning (ML) industry has continued to grow at a rapid rate over recent years. Hidden Technical Debt in Machine Learning Systems More money, more problems — Rise of too many ML tools 2012 vs 2023 — Source: Matt Turck People often believe that money is the solution to a problem.

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Dataconomy

AUGUST 22, 2024

Aleksandr Timashov is an ML Engineer with over a decade of experience in AI and Machine Learning. On these projects, I mentored numerous ML engineers, fostering a culture of innovation within Petronas. You told us you were implementing these projects in 2020-2022, so it all started amid the Covid-19 times.

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KDnuggets

JANUARY 7, 2020

There is a need for a new way to explain complex, ensembled ML models for high-stakes applications such as credit and lending. This is why we invented GIG.

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AWS Machine Learning Blog

OCTOBER 16, 2024

The call processing workflow uses custom machine learning (ML) models built by Intact that run on Amazon Fargate and Amazon Elastic Compute Cloud (Amazon EC2). This pipeline provides self-serving capabilities for data scientists to track ML experiments and push new models to an S3 bucket.

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Data Science 101

JANUARY 24, 2020

Azure SDK January 2020 Updates – The SDK now includes preview support of the Text Analytics capabilities from Cognitive Services. Choosing the Right ML Tools – This video walks thru the Google Machine Learning Decision Pyramid. It is nice to know the level of abstraction for various ML tools in Google Cloud.

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Data Science Dojo

JANUARY 20, 2023

” -DSD- Nothing can compare to Michael Jordan’s announcement in 1995 that he was returning to the NBA, but for Data Science Dojo (DSD), this comes close. In 2020, we had to move our in-person Data Science Bootcamp curriculum to an online format.

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Data Science Dojo

FEBRUARY 6, 2025

billion in 2020 to $4.1 Data annotation is the process of labeling data to make it understandable and usable for machine learning (ML) models. Some key types of data annotation are as follows: Text Annotation Text annotation is the process of labeling and categorizing elements within a text to provide context and meaning for ML models.

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Towards AI

NOVEMBER 16, 2024

We also examine P-STN, a potential upgrade from 2020 including enhanced transformations and increased efficiency. This blog delves into the functional advantages and disadvantages of STNs, despite the extensive coverage in multiple studies.

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KDnuggets

JANUARY 10, 2020

Also: Google's New Explainable AI Service; 10 Free Top Notch Machine Learning Courses.

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Dataconomy

FEBRUARY 26, 2024

GPUs: The versatile powerhouses Graphics Processing Units, or GPUs, have transcended their initial design purpose of rendering video game graphics to become key elements of Artificial Intelligence (AI) and Machine Learning (ML) efforts.

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AWS Machine Learning Blog

DECEMBER 14, 2023

This can significantly shorten the time needed to deploy the Machine Learning (ML) pipeline to production. The following is the sample code to schedule a SageMaker Processing job for a specified day, for example 2020-01-01, using the SageMaker SDK. session.Session().region_name session.Session().region_name

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AWS Machine Learning Blog

SEPTEMBER 4, 2024

Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. Amazon SageMaker provides capabilities to remove the undifferentiated heavy lifting of building and deploying ML models. This entire workflow is shown in the following solution diagram.

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AWS Machine Learning Blog

APRIL 7, 2025

This approach allows for greater flexibility and integration with existing AI and machine learning (AI/ML) workflows and pipelines. By providing multiple access points, SageMaker JumpStart helps you seamlessly incorporate pre-trained models into your AI/ML development efforts, regardless of your preferred interface or workflow.

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Data Science 101

JANUARY 10, 2020

2020 is now in full swing and the announcements are starting to show up. Data Drift Monitoring for Azure ML Datasets Azure ML now provides monitoring for when your data changes (called data drift). Upcoming Online ML/AI Conference, AWS Innovate A free, online conference hosted by Amazon Web Services.

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DataRobot Blog

MARCH 30, 2022

For those who haven’t read the prior blogs ( 2019 , 2020 , 2021 ), the idea behind this task is to leverage various sources of data for each track (betting odds, audio analysis , lyric sentiment) to rank which ones are most likely to win the aforementioned awards. Composable ML. See DataRobot Composable ML in Action.

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AWS Machine Learning Blog

APRIL 5, 2024

SageMaker geospatial capabilities make it straightforward for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. Among these models, the spatial fixed effect model yielded the highest mean R-squared value, particularly for the timeframe spanning 2014 to 2020.

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AWS Machine Learning Blog

MARCH 29, 2023

In this post, we discuss how the IEO developed UNDP’s artificial intelligence and machine learning (ML) platform—named Artificial Intelligence for Development Analytics (AIDA)— in collaboration with AWS, UNDP’s Information and Technology Management Team (UNDP ITM), and the United Nations International Computing Centre (UNICC).

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Applied Data Science

AUGUST 2, 2021

Machine Learning In this section, we look beyond ‘standard’ ML practices and explore the 6 ML trends that will set you apart from the pack in 2021. Give this technique a try to take your team’s ML modelling to the next level. Explainable ML When modelling business process, the why is often more important than the what.

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Tableau

DECEMBER 9, 2020

December 9, 2020 - 7:54pm. December 9, 2020. With something for every line of business and every industry, you’ll have tons of opportunities to learn from customers and peers who have built resilience through 2020—all right from your couch. Ava Kavelle. Product Marketing Manager, Tableau CRM (formerly Einstein Analytics).

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Towards AI

APRIL 6, 2023

Coined after the viral phrase, ‘you only live once’ (YOLO), the machine learning (ML) world first coined this acronym and repurposed it to You Only Look Once — YOLO. The latest installment of the YOLO architecture (YOLOv4) made its debut in April 2020 as the most recent iteration [1].

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ODSC - Open Data Science

MAY 30, 2023

Be sure to check out his talk, “ ML Applications in Asset Allocation and Portfolio Management ,” there! For example, rising interest rates and falling equities already in 2013 and again in 2020 and 2022 led to drawdowns of risk parity schemes. Editor’s note: Peter Schwendner, PhD is a speaker for ODSC Europe this June.

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IBM Journey to AI blog

AUGUST 12, 2024

Wearable devices (such as fitness trackers, smart watches and smart rings) alone generated roughly 28 petabytes (28 billion megabytes) of data daily in 2020. AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps).

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KDnuggets

MARCH 25, 2020

Read our analysis of coronavirus data and poll results; Use your time indoors to learn with 24 best and free books to understand Machine Learning; Study the 9 important lessons from the first year as a Data Scientist; Understand the SVM, a top ML algorithm; check a comprehensive list of AI resources for online learning; and more.

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Flipboard

NOVEMBER 22, 2023

In addition, customers are looking for choices to select the most performant and cost-effective machine learning (ML) model and the ability to perform necessary customization (fine-tuning) to fit their business use cases. RAG combined with LLMs offers a solution to the previously mentioned limitations. Lewis et al.

ML 167

ML ML AWS Machine Learning 167

Tableau

DECEMBER 9, 2020

December 9, 2020 - 7:54pm. December 9, 2020. With something for every line of business and every industry, you’ll have tons of opportunities to learn from customers and peers who have built resilience through 2020—all right from your couch. Ava Kavelle. Product Marketing Manager, Tableau CRM (formerly Einstein Analytics).

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AWS Machine Learning Blog

JANUARY 6, 2023

The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning (ML) model development, including data preparation, model building and training, model operation, evaluation, deployment, and monitoring. AI life-cycle tools are essential to productize AI/ML solutions. AWS position.

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