AWS Machine Learning Blog

JULY 15, 2024

Video auto-dubbing that uses the power of generative artificial intelligence (generative AI ) offers creators an affordable and efficient solution. About the Authors Na Yu is a Lead GenAI Solutions Architect at Mission Cloud, specializing in developing ML, MLOps, and GenAI solutions in AWS Cloud and working closely with customers.

AWS 130

AWS ML ML Big Data 130

AWS Machine Learning Blog

DECEMBER 18, 2023

Amazon SageMaker Canvas Amazon SageMaker Canvas is a visual machine learning (ML) service that enables business analysts and data scientists to build and deploy custom ML models without requiring any ML experience or having to write a single line of code. Through Atlas Data Federation, data is extracted into Amazon S3 bucket.

Clustering 127

Clustering AWS Database ML 127

Flipboard

NOVEMBER 24, 2023

SnapLogic’s AI journey In the realm of integration platforms, SnapLogic has consistently been at the forefront, harnessing the transformative power of artificial intelligence. Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. Sandeep holds an MSc.

Database 158

Database AWS ETL SQL 158

Towards AI

JULY 19, 2023

The Continuing Story of Neural Magic Around New Year’s time, I pondered about the upcoming sparsity adoption and its consequences on inference w/r/t ML models. facebook/wav2vec2-base-960h · Hugging Face We're on a journey to solve and democratize artificial intelligence through natural language. and share with friends!

Natural Language Processing 98

Natural Language Processing Azure Python Artificial Intelligence 98

AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). And finally, some activities, such as those involved with the latest advances in artificial intelligence (AI), are simply not practically possible, without hardware acceleration. Work by Hinton et al.

AWS 118

AWS ML ML Clustering 118

Hacker News

FEBRUARY 24, 2022

The adoption of RISC-V, a free and open-source computer instruction-set architecture first introduced in 2010, is taking off like a rocket. RISC-V seemed like an ideal base to solve a lot of the kinds of computation people wanted to do for artificial intelligence.” We set out to prove all those people wrong,” he says.

AI 139

AI AI Machine Learning Machine Learning 139

O'Reilly Media

SEPTEMBER 19, 2023

Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. But in its early form of a Hadoop-based ML library, Mahout still required data scientists to write in Java. If you wanted ML beyond what Mahout provided, you had to frame your problem in MapReduce terms. What more could we possibly want?

Hadoop 137

Hadoop Algorithm ML ML 137

AWS Machine Learning Blog

SEPTEMBER 27, 2024

We can also gain an understanding of data presented in charts and graphs by asking questions related to business intelligence (BI) tasks, such as “What is the sales trend for 2023 for company A in the enterprise market?” The step-by-step explanation is augmented with few-shot learning examples to develop an initial CloudFormation template.

AWS 129

AWS AI AI Computer Science 129

Towards AI

JULY 21, 2023

The cryptic book arrived on the internet in the mid 2010’s by the now wildly popular but mysterious internet group 3301. It uses the 2 model architecture: sparse search via Elasticsearch and then a ranker ML model.

Natural Language Processing 96

Natural Language Processing ML ML Python 96

O'Reilly Media

FEBRUARY 25, 2025

This meant that at the start of my project I had to instruct Claude to generate mock-up frontend code using those older libraries; otherwise by default it would use modern JavaScript frameworks like React or Svelte that would not integrate well with Python Tutor, which is written using 2010-era jQuery and friends.

AI 87

AI AI Python Computer Science 87

Towards AI

JULY 21, 2023

The Continuing Story of Neural Magic Around New Year’s time, I pondered about the upcoming sparsity adoption and its consequences on inference w/r/t ML models. facebook/wav2vec2-base-960h · Hugging Face We're on a journey to solve and democratize artificial intelligence through natural language. and share with friends!

Natural Language Processing 52

Natural Language Processing Azure Python Artificial Intelligence 52

Mlearning.ai

JULY 20, 2023

The process to calculate the probability of rain involves determining the ratio of the total number of rainy days in June from 2010 to 2022 to the total number of days during the same period. Generates a bar chart depicting the count of rainy days in June from 2010 to 2022. . Filters out the specific Toronto weather station data.

Python 52

Python Algorithm Machine Learning Machine Learning 52

O'Reilly Media

JULY 20, 2021

After the release of the iPad in 2010 Craig Hockenberry discussed the great value of communal computing but also the concerns : “When you pass it around, you’re giving everyone who touches it the opportunity to mess with your private life, whether intentionally or not. This expectation isn’t a new one either.

ML 135

ML ML Machine Learning Machine Learning 135

ML Review

JUNE 4, 2018

Hence, as we shall see, attention mechanisms and reinforcement learning are at the forefront of the latest advances — and their success may one day reduce some of the decision-process opacity that harms other areas of artificial intelligence research. eds) Computer Vision — ECCV 2010. 53] Farhadi et al. In: Daniilidis K.,

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Mlearning.ai

JUNE 18, 2023

References [link] [link] [link] [link] BECOME a WRITER at MLearning.ai // FREE ML Tools // AI Film Critics Mlearning.ai Finally, we showed how to perform the transfer learning process and what the eventual predictions look like. The Jupyter notebook for the code above is available on GitHub.

Deep Learning 52

Deep Learning Deep Learning Python ML 52

Mlearning.ai

JANUARY 31, 2023

2010, doi: 10.1109/TBME.2010.2060723. Handel, J. -O. Nilsson and J. Rantakokko, “ Zero-Velocity Detection — An Algorithm Evaluation ,” in IEEE Transactions on Biomedical Engineering, vol. 2657–2666, Nov. 2010.2060723. [2] 2] Haviland, J. and Corke, P., A purely-reactive manipulability-maximising motion controller.

Clustering 52

Clustering Algorithm Machine Learning Machine Learning 52

DrivenData Labs

SEPTEMBER 10, 2024

Many teams combined technical skills in AI/ML with domain knowledge in neuroscience, aging, or healthcare. He is an expert in biomedical informatics, general artificial intelligence, cutting-edge machine learning algorithms, and the computational aspects of data science.

Machine Learning 147

Machine Learning Machine Learning Computer Science Computer Science 147

O'Reilly Media

APRIL 23, 2024

Google and Amazon were still atop their respective hills of web search and ecommerce in 2010, and Meta’s growth was still accelerating, but it was hard to miss that internet growth had begun to slow. Now a typical page of Amazon product search results consists of 16 ads and only four organic results. The market was maturing.

Algorithm 136

Algorithm AI AI Cloud Computing 136

O'Reilly Media

JULY 25, 2023

To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This choice also inspired me to call my project Swift Papers.

AI 98

AI AI ML ML 98

Hacker News

FEBRUARY 9, 2025

In 2010, grants from the NIH helped launch the Human Connectome Project (HCP) , a five-year effort aimed at mapping the structural and functional connectivity of the human brain using non-invasive techniques such as diffusion MRI (dMRI) and functional MRI (fMRI). Surprisingly, humans are better than ML at spotting these errors.

Algorithm 141

Algorithm Artificial Intelligence Artificial Intelligence AI 141

AWS Machine Learning Blog

FEBRUARY 19, 2025

Rather than using probabilistic approaches such as traditional machine learning (ML), Automated Reasoning tools rely on mathematical logic to definitively verify compliance with policies and provide certainty (under given assumptions) about what a system will or wont do. However, its important to understand its limitations.

AWS 93

AWS Natural Language Processing Machine Learning Machine Learning 93