Hacker News

MARCH 25, 2022

First described in a 2017 paper from Google, transformers are among the newest and one of the most powerful classes of models invented to date. They’re driving a wave of advances in machine learning some have dubbed transformer AI. Now we see self-attention is a powerful, flexible tool for learning,” he added. “Now

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Dataconomy

OCTOBER 2, 2024

Kingma, is a prominent figure in the field of artificial intelligence and machine learning. cum laude in machine learning from the University of Amsterdam in 2017. His academic work, particularly in deep learning and generative models, has had a profound impact on the AI community. He earned his Ph.D.

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Towards AI

NOVEMBER 18, 2024

When I started learning about machine learning and deep learning in my pre-final year of undergrad in 2017–18, I was amazed by the potential of these models. Image by ChatGPT You know how in sci-fi movies, AI systems seamlessly collaborate to solve complex problems? This always used to fascinate me as a kid.

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Towards AI

AUGUST 25, 2023

DL Artificial intelligence (AI) is the study of ways to build intelligent programs and machines that can creatively solve problems, which has always been considered a human prerogative. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

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Towards AI

NOVEMBER 16, 2024

This blog explores how Keswani’s method addresses common challenges in min-max scenarios, with applications in areas of modern Machine Learning such as GANs, adversarial training, and distributed computing, providing a robust alternative to traditional algorithms like Gradient Descent Ascent (GDA). 214–223, 2017.[4] Makelov, L.

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PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

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Heartbeat

NOVEMBER 8, 2023

Photo by Manki Kim on Unsplash Introduction Machine learning is a complex process that involves many different steps, including data gathering, preprocessing, model selection, hyperparameter tuning, and performance evaluation. In a modest machine learning project, it may take a lot of work to manage these processes.

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Mlearning.ai

FEBRUARY 10, 2023

For example, if you are using regularization such as L2 regularization or dropout with your deep learning model that performs well on your hold-out-cross-validation set, then increasing the model size won’t hurt performance, it will stay the same or improve. In the big data and deep learning era, now you have much more flexibility.

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Explosion

JANUARY 12, 2018

While we wouldn’t say bootstrapping is for everyone, it’s been a joy to build the company that we want to build, the way we want to build it: Worked with some amazing companies and shipped custom, cutting-edge machine learning solutions for a range of exciting problems. spaCy’s Machine Learning library for NLP in Python.

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Mlearning.ai

JUNE 7, 2023

Hey, guys in this blog we will see some of the Best End to End Machine Learning Projects with source codes. This is going to be an interesting blog, so without any further due, let’s start… Machine learning has revolutionized various industries, from healthcare to finance and everything in between.

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Towards AI

JUNE 6, 2023

Now it’s possible to have deep learning models with no limitation for the input size. unsplash Attention-based transformers have revolutionized the AI industry since 2017. Last Updated on June 8, 2023 by Editorial Team Author(s): Reza Yazdanfar Originally published on Towards AI.

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Mlearning.ai

MAY 23, 2023

Hey guys, we will see some of the Best and Unique Machine Learning Projects for final year engineering students in today’s blog. Machine learning has become a transformative technology across various fields, revolutionizing complex problem-solving. final year Machine learning project.

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ODSC - Open Data Science

OCTOBER 18, 2023

Many companies are now utilizing data science and machine learning , but there’s still a lot of room for improvement in terms of ROI. Nevertheless, we are still left with the question: How can we do machine learning better? billion in 2022, an increase of 21.3%

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Mlearning.ai

MAY 21, 2023

Hey guys, we will see some of the Best and Unique Machine Learning Projects with Source Codes in today’s blog. If you are interested in exploring machine learning and want to dive into practical implementation, working on machine learning projects with source code is an excellent way to start.

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Dataconomy

FEBRUARY 6, 2024

Artificial intelligence and machine learning are no longer the elements of science fiction; they’re the realities of today. According to Precedence Research , the global market size of machine learning will grow at a CAGR of a staggering 35% and reach around $771.38 billion by 2032. billion by 2032.

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AssemblyAI

MARCH 21, 2023

What are the actual advantages of Graph Machine Learning? This article will recap on some highly impactful applications of GNNs, the first article in a series that will take a deep dive into Graph Machine Learning, giving you everything you need to know to get up to speed on the next big wave in AI.

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DataRobot Blog

MARCH 9, 2022

With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task. Whenever you test a machine learning method, it’s helpful to have a baseline method and accuracy level against which to measure improvements. It provides 1.6

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Heartbeat

MARCH 14, 2023

Some of the methods used for scene interpretation include Convolutional Neural Networks (CNNs) , a deep learning-based methodology, and more conventional computer vision-based techniques like SIFT and SURF. A combination of simulated and real-world data was used to train the system, enabling it to generalize to new objects and tasks.

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Mlearning.ai

JUNE 6, 2023

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This list will consist of Machine learning projects, Deep Learning Projects, Computer Vision Projects , and all other types of interesting projects with source codes also provided.

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Dataconomy

OCTOBER 3, 2023

These platforms offer an ideal environment for delving into subjects like machine learning, image recognition, and computer vision, and yes, for a touch of entertainment as well. The tool leverages sophisticated machine learning techniques and human image synthesis to craft realistic face replacements in videos.

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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. Citation: Article from IBM archives 2.

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Mlearning.ai

JANUARY 27, 2023

Save this blog for comprehensive resources for computer vision Source: appen Working in computer vision and deep learning is fantastic because, after every few months, someone comes up with something crazy that completely changes your perspective on what is feasible. Template Matching —  Video Tutorial , Written Tutorial 12.

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Applied Data Science

JANUARY 4, 2022

At the very least, we hope that by reading this list you can cross-out “Learning about the state of AI in 2021” from your resolution list ?. ? Transformers taking the AI world by storm The family of artificial neural networks (ANNs) saw a new member being born in 2017, the Transformer. What happens when you combine the two?

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Towards AI

JUNE 4, 2023

BERT Transformer Source: Image created by the author + Stable Diffusion (All Rights Reserved) In the context of machine learning and NLP, a transformer is a deep learning model introduced in a paper titled “Attention is All You Need” by Vaswani et al.

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Heartbeat

DECEMBER 4, 2023

The challenges and successes involved in bringing AI to your palm Photo by Neil Soni on Unsplash The proliferation of machine learning and deep learning algorithms has been ubiquitous and has not left any device with an ounce of processing power behind, even our smartphones.

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Mlearning.ai

MARCH 31, 2023

In this story, we talk about how to build a Deep Learning Object Detector from scratch using TensorFlow. The Recipe Roughly speaking, 99% of machine learning projects consist on a simple recipe: define a model , get a bunch of data , and choose the metrics used to train and evaluate the model.

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Defined.ai blog

JANUARY 29, 2023

Generative Adversarial Networks (GANs) are a type of deep learning algorithm that’s been gaining popularity due to their ability to generate high-quality, realistic images and other types of data. As such, Generative Adversarial Networks are invaluable deep learning algorithms with almost endless beneficial potential.

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DrivenData Labs

DECEMBER 11, 2024

The startup cost is now lower to deploy everything from a GPU-enabled virtual machine for a one-off experiment to a scalable cluster for real-time model execution. Deep learning - It is hard to overstate how deep learning has transformed data science. Data science, machine learning and AI rely on data.

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Towards AI

JULY 20, 2023

It’s also an area that stands to benefit most from automated or semi-automated machine learning (ML) and natural language processing (NLP) techniques. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al. dollars apiece.

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AWS Machine Learning Blog

JUNE 8, 2023

LLMs are based on the Transformer architecture , a deep learning neural network introduced in June 2017 that can be trained on a massive corpus of unlabeled text. This enables you to begin machine learning (ML) quickly. It includes the FLAN-T5-XL model , an LLM deployed into a deep learning container.

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Data Science Dojo

AUGUST 16, 2023

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.

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Data Science Dojo

AUGUST 16, 2023

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.

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AWS Machine Learning Blog

MAY 16, 2024

In this post, we share how LotteON improved their recommendation service using Amazon SageMaker and machine learning operations (MLOps). Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships.

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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. Advances in neural information processing systems 30 (2017).

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ML Review

MARCH 31, 2019

Are the machine learning models we use intrinsically flawed? Up to this point, machine learning algorithms simply didn’t work well enough for anyone to be surprised when it failed to do the right thing. Kurakin et al, ICLR 2017. Source: Robust Physical-World Attacks on Deep Learning Visual Classification.

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Towards AI

APRIL 19, 2024

Amazon (AWS) 👉Industry domain: Online retail and web services provider 👉Location: Over 175 Amazon fulfillment centers globally 👉Year founded: 1994 👉Key Products developed: Amazon Bedrock, Q, Code Whisperer, Sage Maker 👉Benefits: Fully managed generative AI service options, AWS free tier for experimentation 7.

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Explosion

FEBRUARY 12, 2017

In this post, I’ll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. The SNLI dataset is over 100x larger than previous similar resources, allowing current deep-learning models to be applied to the problem.

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