IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

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Marktechpost

AUGUST 3, 2024

The researchers control parameters and FLOPs for both network types, evaluating their performance across diverse domains, including symbolic formula representation, machine learning, computer vision, natural language processing, and audio processing.

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Analytics Vidhya

JUNE 5, 2019

Introduction If I had to pick one platform that has single-handedly kept me up-to-date with the latest developments in data science and machine learning. The post Top 7 Machine Learning Github Repositories for Data Scientists appeared first on Analytics Vidhya.

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Analytics Vidhya

AUGUST 1, 2019

Overview Looking for machine learning projects to do right now? Here are 7 wide-ranging GitHub projects to try out These projects cover multiple machine. The post 7 Innovative Machine Learning GitHub Projects you Should Try Out in Python appeared first on Analytics Vidhya.

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Unite.AI

NOVEMBER 5, 2024

The need for specialized AI accelerators has increased as AI applications like machine learning, deep learning , and neural networks evolve. NVIDIA has been the dominant player in this domain for years, with its powerful Graphics Processing Units (GPUs) becoming the standard for AI computing worldwide.

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Analytics Vidhya

DECEMBER 22, 2019

Overview A comprehensive look at the top machine learning highlights from 2019, including an exhaustive dive into NLP frameworks Check out the machine learning. The post 2019 In-Review and Trends for 2020 – A Technical Overview of Machine Learning and Deep Learning!

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Analytics Vidhya

DECEMBER 25, 2023

They have emerged as a groundbreaking approach, revolutionizing how machines perceive and understand the world. Combining the strengths of computer vision and Natural Language Processing (NLP), multimodal models open up new possibilities for machines to interact with the environment in a more human-like manner.

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AI News

APRIL 8, 2024

The popular ML Olympiad is back for its third round with over 20 community-hosted machine learning competitions on Kaggle. This year’s lineup includes challenges spanning areas like healthcare, sustainability, natural language processing (NLP), computer vision, and more.

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Towards AI

JULY 17, 2023

Natural language processing, computer vision, machine learning I recently moved from the computer vision (CV) domain to the natural language processing (NLP) domain and found some interesting observations. NLP is language-specific, but CV is not. However, computer vision is much easier.

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Analytics Vidhya

DECEMBER 28, 2021

This article was published as a part of the Data Science Blogathon Photo by Hush Naidoo Jade Photography Pre-requisite: Basic understanding of Python, Deep Learning, Classification, and Computer Vision Deep learning is a subset of machine learning and has been applied in various fields to help solve existing problems.

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Unite.AI

DECEMBER 12, 2024

This includes developments in natural language processing (NLP) , computer vision , and machine learning that power current services like Bedrock and Q Business. The team is not starting from scratch but building upon foundation models and technologies already developed by Amazon's broader AI teams.

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IBM Journey to AI blog

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

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Unite.AI

OCTOBER 27, 2023

In this article, we will delve deeper into 3D computer vision and the Uni3D framework, exploring the essential concepts and the architecture of the model. Uni3D and 3D Representation Learning : An Introduction In the past few years, computer vision has emerged as one of the most heavily invested domains in the AI industry.

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Unite.AI

APRIL 6, 2025

Wendys AI-Powered Drive-Thru System (FreshAI) FreshAI uses advanced natural language processing (NLP) , machine learning (ML) , and generative AI to optimize the fast-food ordering experience.

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Aiiot Talk

MAY 6, 2023

AI comprises numerous technologies like deep learning, machine learning, natural language processing, and computer vision. With the help of these technologies, AI is now capable of learning, reasoning, and processing complex data. This improvement has led to a significant advancement in medical diagnosis.

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IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

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Marktechpost

MARCH 30, 2024

In 2024, the landscape of Python libraries for machine learning and deep learning continues to evolve, integrating more advanced features and offering more efficient and easier ways to build, train, and deploy models. PyTorch PyTorch is a widely used open-source machine learning library based on the Torch library.

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ODSC - Open Data Science

FEBRUARY 10, 2025

A/V analysis and detection are some of machine learnings most practical applications. adults use only work when they can turn audio data into words, and then apply natural language processing (NLP) to understand it. Choose an Appropriate Algorithm As with all machine learning processes, algorithm selection is also crucial.

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Marktechpost

NOVEMBER 22, 2023

Natural language processing (NLP) is a good example of this tendency since sophisticated models demonstrate flexibility with thorough knowledge covering several domains and tasks with straightforward instructions. The popularity of NLP encourages a complementary strategy in computer vision.

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Viso.ai

DECEMBER 20, 2023

In the field of computer vision, supervised learning and unsupervised learning are two of the most important concepts. In this guide, we will explore the differences and when to use supervised or unsupervised learning for computer vision tasks. What is supervised learning? About us: Viso.ai

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Unite.AI

AUGUST 2, 2023

Machine learning models have heavily relied on labeled data for training, and traditionally speaking, training models on labeled data yields accurate results. To tackle the annotation issue, developers came up with the concept of SSL or Self Supervised Learning. They require a high amount of computational power.

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Marktechpost

OCTOBER 25, 2024

Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. As NLP continues to advance, there is a growing need for skilled professionals to develop innovative solutions for various applications, such as chatbots, sentiment analysis, and machine translation.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed.

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Towards AI

JANUARY 31, 2025

Since then, explainability has become an essential part of the development process, especially in machine learning field. However, the term Black box can be seen frequently in Deep learning as the Black-box models are the ones that are difficult to interpret.

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Towards AI

DECEMBER 16, 2024

From breakthroughs in large language models to revolutionary approaches in computer vision and AI safety, the research community has outdone itself. Vision Mamba Summary: Vision Mamba introduces the application of state-space models (SSMs) to computer vision tasks. And lets be real what a year it has been!

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Analytics Vidhya

FEBRUARY 24, 2021

ArticleVideo Book Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. The post A Comprehensive Step-by-Step Guide to Become an Industry Ready Data Science Professional appeared first on Analytics Vidhya.

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Marktechpost

OCTOBER 18, 2023

The recent results of machine learning in drug discovery have been largely attributed to graph and geometric deep learning models. Like other deep learning techniques, they need a lot of training data to provide excellent modeling accuracy. If you like our work, you will love our newsletter. We are also on WhatsApp.

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Machine Learning Deep Learning Neural Network Natural Language Processing 124

Marktechpost

DECEMBER 1, 2023

Computer vision, NLP, and other domains have seen remarkable success with deep machine learning (ML) approaches based on deep neural networks (NNs). The post Researchers Study Tensor Networks for Interpretable and Efficient Quantum-Inspired Machine Learning appeared first on MarkTechPost.

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IBM Journey to AI blog

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. This allows intelligent machines to identify and classify objects within images and video footage.

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Unite.AI

AUGUST 28, 2023

AI can receive and process a wide range of information thanks to a combination of sophisticated sensory devices and computer vision. An improved outcome is produced by enhancing the data with machine learning (ML) and natural language processing (NLP).

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Marktechpost

FEBRUARY 23, 2025

Recent studies have addressed this gap by introducing benchmarks that evaluate AI agents on various software engineering and machine learning tasks. The benchmark, MLGym-Bench, includes 13 open-ended tasks spanning computer vision, NLP, RL, and game theory, requiring real-world research skills.

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Marktechpost

MARCH 11, 2024

However, understanding their information-flow dynamics, learning mechanisms, and interoperability remains challenging, limiting their applicability in sensitive domains requiring explainability. In our work, "The Hidden Attention of Mamba Models" we provide answers to these questions! [1/4]

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Marktechpost

FEBRUARY 27, 2024

Recent advancements in generative deep learning models have revolutionized fields such as Natural Language Processing (NLP) and Computer Vision (CV). Join our 38k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Machine Learning 131

Machine Learning Natural Language Processing Computer Vision NLP 131

AWS Machine Learning Blog

NOVEMBER 10, 2023

In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML knowledge for creating and tuning of deep learning models. The integration eliminates the need for any coding or data engineering to use the robust NLP models of Amazon Comprehend.

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AWS Machine Learning Blog

MARCH 5, 2025

However, traditional machine learning approaches often require extensive data-specific tuning and model customization, resulting in lengthy and resource-heavy development. He builds machine learning pipelines and recommendation systems for product recommendations on the Detail Page.

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Marktechpost

AUGUST 24, 2023

In the fast-paced world of Artificial Intelligence (AI) and Machine Learning, staying updated with the latest trends, breakthroughs, and discussions is crucial. Here’s our curated list of the top AI and Machine Learning-related subreddits to follow in 2023 to keep you in the loop. With over 2.5 It has over 37.4k

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Marktechpost

DECEMBER 24, 2023

Self-attention greatly enhances the performance of transformers in real-world applications, including computer vision and Natural Language Processing (NLP). The post This Machine Learning Research Opens up a Mathematical Perspective on the Transformers appeared first on MarkTechPost.

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