Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Deep Learning?

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Dataconomy

MAY 25, 2023

The integration of artificial intelligence in Internet of Things introduces new dimensions of efficiency, automation, and intelligence to our daily lives. Simultaneously, artificial intelligence has revolutionized the way machines learn, reason, and make decisions.

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Mlearning.ai

JULY 11, 2023

Deep learning has transformed artificial intelligence, allowing machines to learn and make smart decisions. If you’re interested in exploring deep learning, this step-by-step guide will help you learn the basics and develop the necessary skills.

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Dataconomy

OCTOBER 5, 2023

If you are interested in technology at all, it is hard not to be fascinated by AI technologies. Artificial intelligence, one of the most talked about topics in today’s technology world, has played a huge role in bringing many things into our lives, especially in the last five years. Firstly, data collection is essential.

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Dataversity

DECEMBER 16, 2022

2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning. Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements.

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Data Science Blog

MARCH 14, 2023

Von Big Data über Data Science zu AI Einer der Gründe, warum Big Data insbesondere nach der Euphorie wieder aus der Diskussion verschwand, war der Leitspruch “S**t in, s**t out” und die Kernaussage, dass Daten in großen Mengen nicht viel wert seien, wenn die Datenqualität nicht stimme. Artificial Intelligence (AI) ersetzt.

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PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision. Also, you might want to check out our computer vision for deep learning program before you go.

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Towards AI

AUGUST 29, 2023

Last Updated on August 30, 2023 by Editorial Team Author(s): Tan Pengshi Alvin Originally published on Towards AI. Introducing the backbone of Reinforcement Learning — The Markov Decision Process This member-only story is on us. Join thousands of data leaders on the AI newsletter. Published via Towards AI

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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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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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ODSC - Open Data Science

JULY 26, 2023

Machine learning is a subfield of artificial intelligence (AI) that enables computers to learn and make decisions or predictions without explicit programming. There are three main types of machine learning : supervised learning, unsupervised learning, and reinforcement learning.

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ODSC - Open Data Science

AUGUST 10, 2023

In the rapidly evolving field of artificial intelligence, agents that can effectively interact with humans and navigate the complexities of the real world are highly sought after. Current agent models often learn to follow simple language instructions for specific tasks , driven by rewards. Save your seat and register today.

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IBM Journey to AI blog

MAY 9, 2023

We stand on the frontier of an AI revolution. Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know.

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IBM Journey to AI blog

JUNE 14, 2023

Sometimes the problem with artificial intelligence (AI) and automation is that they are too labor intensive. Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. This is an open, hard problem for the entire field of AI applications.

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ODSC - Open Data Science

MARCH 22, 2023

Be sure to check out his session, “ Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI ,” there! What exactly is data-centric AI? Data-centric AI instead asks how we can systematically engineer better data through algorithms/automation. A common gripe I hear is: “Garbage in, garbage out.

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AssemblyAI

SEPTEMBER 12, 2023

Automatic Speech Recognition, or ASR, is the use of Machine Learning or Artificial Intelligence (AI) technology to process human speech into readable text. In 2014, Baidu published the paper, Deep Speech: Scaling up end-to-end speech recognition. The data does not need to be force-aligned.

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Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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Smart Data Collective

JUNE 4, 2021

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Basics of Machine Learning. Machine learning is the science of building models automatically. It is a branch of artificial intelligence. In supervised learning, a variable is predicted.

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Data Science Dojo

SEPTEMBER 11, 2023

The developers have taken a proactive stance to ensure responsible AI practices are embedded in PaLM 2’s functionality. Real-World Applications and Use Cases of PaLM 2: The features and capabilities of PaLM 2’s model extends to a myriad of real-world applications, revolutionizing and changing the way we interact with technology.

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Dataconomy

MARCH 14, 2023

In recent years, natural language processing and conversational AI have gained significant attention as technologies that are transforming the way we interact with machines and each other. These fields involve the use of machine learning and artificial intelligence to enable machines to understand, interpret, and generate human language.

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ODSC - Open Data Science

FEBRUARY 10, 2023

What worked best was an algorithm that combined two sub-fields of machine learning, supervised learning, and unsupervised learning. With these results, the team is optimistic that with the help of AI, life outside of our planet can be found. which together can go through large datasets in search of hidden patterns.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. Artificial intelligence is the overarching system.

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Hacker News

MARCH 25, 2022

If you want to ride the next big wave in AI, grab a transformer. A transformer model is a neural network that learns context and thus meaning by tracking relationships in sequential data like the words in this sentence. They’re driving a wave of advances in machine learning some have dubbed transformer AI.

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IBM Journey to AI blog

JULY 6, 2023

What is machine learning? Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Machine learning can then “learn” from the data to create insights that improve performance or inform predictions.

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Dataconomy

MARCH 27, 2023

Robotic process automation vs machine learning is a common debate in the world of automation and artificial intelligence. The differences between robotic process automation vs machine learning lie in their functionality, purpose, and the level of human intervention required Is RPA artificial intelligence?

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Becoming Human

AUGUST 15, 2023

Logistic regression is a type of supervised learning algorithm. My research focuses on developing robust deep learning models for solving computer vision problems. In this blog, we will break down the concept of logistic regression and explain it as simply as possible. What is Logistic Regression?

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PyImageSearch

FEBRUARY 6, 2023

If you are a regular PyImageSearch reader and have even basic knowledge of Deep Learning in Computer Vision, then this tutorial should be easy to understand. Furthermore, this tutorial acts as a foundation for the following tutorial, where we learn to deploy this trained image classification model on OAK-D. That’s not the case.

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? Explain how you would implement transfer learning in a deep learning model.

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Dataconomy

MARCH 27, 2023

Robotic process automation vs machine learning is a common debate in the world of automation and artificial intelligence. The differences between robotic process automation vs machine learning lie in their functionality, purpose, and the level of human intervention required Is RPA artificial intelligence?

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Becoming Human

MARCH 16, 2023

AI drug discovery is exploding. Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. AI has already helped identify promising candidate therapeutics, and it didn’t take years but months or even days. We will look at success stories, AI benefits, and limitations.

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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. One way to overcome this challenge is through self-supervised learning (SSL). Jeremy Anderson is a Director & Data Scientist at Travelers on the AI & Automation Accelerator team.

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Mlearning.ai

JULY 17, 2023

Data Scientists spend a lot of time and resources in improving the architecture of their AI Models. One of the most promising avenues for this kind of research is to learn from evolution and biological systems to improve the design of AI Models (after all Neural Networks were based on our brains). About the Author: William A.

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Pickl AI

JANUARY 12, 2023

Course Overview : Python Pandas Statistics Introduction to Machine Learning Supervised Learning 1 Supervised Learning 2 Unsupervised Learning Course Eligibility To be eligible for the Data Science course for working professionals, an individual must have worked in an organization for a certain number of years.

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NYU Center for Data Science

MAY 31, 2023

CDS Assistant Professor/Faculty Fellow Jacopo Cirrone works at the intersection of machine learning and healthcare, recently publishing two papers that expand deep learning research within these fields. To learn more about data science’s future in medical imaging and healthcare, CDS spoke with Jacopo.

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IBM Journey to AI blog

DECEMBER 20, 2023

That’s why diversifying enterprise AI and ML usage can prove invaluable to maintaining a competitive edge. What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

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DrivenData Labs

JUNE 14, 2023

¶ Participants in the Meta AI Video Similarity Challenge found creative ways to improve representations used for copy detection, as well as localization techniques that allow copied sections to be identified efficiently within longer videos. In December 2022, DrivenData and Meta AI launched the Video Similarity Challenge.

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