AssemblyAI

NOVEMBER 9, 2023

In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. The models are powered by advanced Deep Learning and Machine Learning research. What is Text Summarization for NLP?

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Bugra Akyildiz

FEBRUARY 26, 2025

Stanford CS224n: Natural Language Processing with Deep Learning Stanford’s CS224n stands as the gold standard for NLP education, offering a rigorous exploration of neural architectures, sequence modeling, and transformer-based systems. S191: Introduction to Deep Learning MIT’s 6.S191

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Marktechpost

MAY 20, 2024

Deep learning is a subset of machine learning that involves training neural networks with multiple layers to recognize patterns and make data-based decisions. This article lists the top courses in deep learning that provide comprehensive knowledge and practical skills necessary to excel in this transformative field.

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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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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. Deep learning algorithms have brought a massive improvement in medical imaging diagnosis.

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Marktechpost

APRIL 12, 2024

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models. It was introduced in the paper “Attention is All You Need” by Vaswani et al.

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Towards AI

JANUARY 29, 2025

Generative AI is powered by advanced machine learning techniques, particularly deep learning and neural networks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). These are essential for understanding machine learning algorithms. Why Become a Generative AI Engineer in 2025?

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Towards AI

JANUARY 31, 2025

Explaining a black box Deep learning model is an essential but difficult task for engineers in an AI project. Explainability leverages user interfaces, charts, business intelligence tools, some explanation metrics, and other methodologies to discover how the algorithms reach their conclusions. This member-only story is on us.

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Unite.AI

SEPTEMBER 18, 2023

Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more. NLP in particular has been a subfield that has been focussed heavily in the past few years that has resulted in the development of some top-notch LLMs like GPT and BERT.

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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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Unite.AI

SEPTEMBER 25, 2023

Initially, the attempts were simple and intuitive, with basic algorithms creating monotonous tunes. However, as technology advanced, so did the complexity and capabilities of AI music generators, paving the way for deep learning and Natural Language Processing (NLP) to play pivotal roles in this tech.

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Marek Rei

NOVEMBER 4, 2024

The prompts are updated by randomly sampling permutations to the existing prompts, then approximating the gradient using the natural evolution strategy (NAS) algorithm. Mind the gap: Challenges of deep learning approaches to Theory of Mind Jaan Aru, Aqeel Labash, Oriol Corcoll, Raul Vicente. Nature Communications 2024.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise.

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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Towards AI

FEBRUARY 3, 2025

DeepSeek AI is an advanced AI genomics platform that allows experts to solve complex problems using cutting-edge deep learning, neural networks, and natural language processing (NLP). DeepSeek AI can learn and improve over time, as opposed to being governed by static, pre-defined principles. Lets begin!

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Analytics Vidhya

JULY 22, 2020

Overview As the size of the NLP model increases into the hundreds of billions of parameters, so does the importance of being able to. The post MobileBERT: BERT for Resource-Limited Devices appeared first on Analytics Vidhya.

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Unite.AI

OCTOBER 3, 2024

Using deep learning algorithms, neural machine translation considers whole sentences simultaneously. It uses deep learning models to analyze and translate metaphors, ensuring they maintain the original's emotional and artistic integrity. Quality control is a critical activity of the process.

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Unite.AI

JANUARY 18, 2025

This parallelism is critical for deep learning tasks, where training and inference involve large batches of data. This design is particularly effective for tasks like: Image Recognition and Processing Natural Language Processing (NLP) and Speech Recognition Object Detection and Autonomous Navigation Generative AI (e.g.,

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Towards AI

JULY 21, 2023

Photo by adrianna geo on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 08.23.20 If you haven’t heard, we released the NLP Model Forge ? NLP Model Forge So… the NLP Model Forge, a collection of 1,400 NLP code snippets that you can seamlessly select to run inference in Colab!

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Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. An algorithm, essentially a set of procedures, learns to identify patterns from a large set of examples (training data). The culmination of this training is a machine-learning model.

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AI Weekly

APRIL 11, 2024

And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses. Generative AI is igniting a new era of innovation within the back office.

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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Unite.AI

JUNE 28, 2023

It uses sophisticated Natural Language Processing (NLP) technology to transform a user's descriptive language into a 3D model. Features of Masterpiece Studio: AI-powered text-to-3D generation User-friendly interface Natural Language Processing (NLP) technology Generates fully functional 3D models and animations 3.

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IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. What makes a good AI conversationalist?

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PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

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The MLOps Blog

MARCH 23, 2023

NLP models in commercial applications such as text generation systems have experienced great interest among the user. These models have achieved various groundbreaking results in many NLP tasks like question-answering, summarization, language translation, classification, paraphrasing, et cetera.

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Unite.AI

OCTOBER 12, 2023

research scientist with over 16 years of professional experience in the fields of speech/audio processing and machine learning in the context of Automatic Speech Recognition (ASR), with a particular focus and hands-on experience in recent years on deep learning techniques for streaming end-to-end speech recognition.

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John Snow Labs

JUNE 2, 2023

Spark NLP’s deep learning models have achieved state-of-the-art results on sentiment analysis tasks, thanks to their ability to automatically learn features and representations from raw text data. Spark NLP has multiple approaches for detecting the sentiment (which is actually a text classification problem) in a text.

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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

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. As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. This study by Bui et al.

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Analytics Vidhya

MARCH 20, 2022

LSTM is a deep-learning-based classifier, and it takes a considerable amount of time to train it. This article was published as a part of the Data Science Blogathon. Introduction In my last article (Sentiment Analysis with LSTM), we discussed what sentiment analysis is and how to perform it using LSTM.

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Marktechpost

JUNE 3, 2024

Its AI courses offer hands-on training for real-world applications, enabling learners to effectively use Intel’s portfolio in deep learning, computer vision, and more. Introduction to Machine Learning This course covers machine learning basics, including problem-solving, model building, and key algorithms.

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Unite.AI

JUNE 2, 2023

Phrasee uses deep learning to generate and optimize email subject lines that maximize open rates and click-through rates. With its natural language processing (NLP) and understanding (NLU), it ensures that all content resonates with your audience in a human-like manner.

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Towards AI

FEBRUARY 6, 2025

to Artificial Super Intelligence and black box deep learning models. This article explores the potential pathways to Artificial Super Intelligence (ASI), examining scaled-up deep learning, neuro-symbolic AI, cognitive architectures, whole brain emulation, and evolutionary algorithms. Enjoy the read!

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Analytics Vidhya

JULY 22, 2024

Introduction In this article, we dive into the top 10 publications that have transformed artificial intelligence and machine learning. We’ll take you through a thorough examination of recent advancements in neural networks and algorithms, shedding light on the key ideas behind modern AI.

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Unite.AI

AUGUST 29, 2024

Sentiment Analytics in High-Frequency Trading Integrating sentiment analytics with algorithmic trading has reshaped how financial markets operate, especially high-frequency trading. Algorithms can adapt to market shifts and allow traders to seize opportunities by tapping into real-time data.

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