Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Explainability is essential for accountability, fairness, and user confidence. Transparency is fundamental for responsible AI usage.

Composite AI 182

Composite AI Explainability Black Box AI Explainable AI 182

Unite.AI

NOVEMBER 6, 2023

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

Marktechpost

JULY 22, 2024

Authorship Verification (AV) is critical in natural language processing (NLP), determining whether two texts share the same authorship. With deep learning models like BERT and RoBERTa, the field has seen a paradigm shift. This lack of explainability is a gap in academic interest and a practical concern.

Explainability 104

Explainability BERT Large Language Models Deep Learning 104

Towards AI

FEBRUARY 6, 2025

to Artificial Super Intelligence and black box deep learning models. Whats AI Weekly The vast majority of what we call Agents are simply an API call to a language model. It highlights the importance of explainability and interpretability for various stakeholders, including data scientists, business leaders, and regulators.

Deep Learning 73

Deep Learning Computer Vision Large Language Models Explainability 73

Marktechpost

APRIL 5, 2024

King’s College London researchers have highlighted the importance of developing a theoretical understanding of why transformer architectures, such as those used in models like ChatGPT, have succeeded in natural language processing tasks. Check out the Paper. Also, don’t forget to follow us on Twitter.

Neural Network 127

Neural Network Natural Language Processing Categorization Explainability 127

IBM Journey to AI blog

JUNE 26, 2023

Possibilities are growing that include assisting in writing articles, essays or emails; accessing summarized research; generating and brainstorming ideas; dynamic search with personalized recommendations for retail and travel; and explaining complicated topics for education and training. What is generative AI? What is watsonx.governance?

Generative AI 203

Generative AI Explainability Explainable AI Natural Language Processing 203

Marktechpost

MARCH 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 142

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 142

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.

Computer Vision 90

Computer Vision Deep Learning Neural Network Artificial Intelligence 90

AWS Machine Learning Blog

FEBRUARY 28, 2025

As organizations adopt AI and machine learning (ML), theyre using these technologies to improve processes and enhance products. AI use cases include video analytics, market predictions, fraud detection, and natural language processing, all relying on models that analyze data efficiently.

DevOps 110

DevOps AI AI Deep Learning 110

ODSC - Open Data Science

MARCH 10, 2025

By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow. The Deep Learning Boom (20182019) Between 2018 and 2019, deep learning dominated the conference landscape.

Data Science 52

Data Science Neural Network Convolutional Neural Networks Large Language Models 52

Marktechpost

MAY 5, 2024

It covers topics such as clustering, predictive modeling, and advanced methods like ensemble learning using the scikit-learn toolkit. Participants also gain hands-on experience with open-source frameworks and libraries like TensorFlow and Scikit-learn. and demonstrates their application in various real-world applications.

Machine Learning 120

Machine Learning Python Neural Network Convolutional Neural Networks 120

IBM Journey to AI blog

MARCH 27, 2024

However, while spend-based commodity-class level data presents an opportunity to help address the difficulties associates with Scope 3 emissions accounting, manually mapping high volumes of financial ledger entries to commodity classes is an exceptionally time-consuming, error-prone process. This is where LLMs come into play.

ESG 238

ESG Categorization Large Language Models NLP 238

AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). In this example, we use the DBpedia Ontology dataset.

Explainability 97

Explainability Algorithm Natural Language Processing Machine Learning 97

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?

NLP 256

NLP AI Modeling Machine Learning AI 256

Heartbeat

FEBRUARY 9, 2023

Photo by Brooks Leibee on Unsplash Introduction Natural language processing (NLP) is the field that gives computers the ability to recognize human languages, and it connects humans with computers. SpaCy is a free, open-source library written in Python for advanced Natural Language Processing.

Natural Language Processing 52

Natural Language Processing Python NLP Deep Learning 52

Marktechpost

JUNE 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 117

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 117

AWS Machine Learning Blog

DECEMBER 12, 2024

To further explain each of these benefits, we demonstrate with examples in the following sections, and finally show you how to set up and run distributed training for the Meta Llama 3.1 8B model using the new ModelTrainer class. This is usually achieved by providing the right set of parameters when using an Estimator.

ML 100

ML Python Data Scientist Natural Language Processing 100

Heartbeat

JULY 18, 2023

Source: Author Natural Language Processing (NLP) is a field of study focused on allowing computers to understand and process human language. There are many different NLP techniques and tools available, including the R programming language.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning ML 52

Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk These applications also leverage the power of Machine Learning and Deep Learning. """

Natural Language Processing 52

Natural Language Processing NLP Deep Learning Machine Learning 52

Unite.AI

NOVEMBER 1, 2023

In an effort to enhance the efficiency of software engineering, including the effectiveness of software and reduced development costs, scientists are exploring the use of deep-learning-based frameworks to tackle various tasks within the software development process. There are two major causes of code hallucinations.

Software Development 264

Software Development Large Language Models LLM Natural Language Processing 264

PyImageSearch

FEBRUARY 17, 2025

Course information: 86+ total classes 115+ hours hours of on-demand code walkthrough videos Last updated: February 2025 4.84 (128 Ratings) 16,000+ Students Enrolled I strongly believe that if you had the right teacher you could master computer vision and deep learning. Or has to involve complex mathematics and equations?

Computer Vision 75

Computer Vision Deep Learning Data Ingestion AI 75

Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. Deep learning-based models, especially CNNs, have revolutionized feature extraction in image captioning.

Natural Language Processing 52

Natural Language Processing Computer Vision NLP Algorithm 52

Marktechpost

NOVEMBER 16, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 107

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 107

IBM Journey to AI blog

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. Scale AI workloads, for all your data, anywhere with watsonx.data Enable responsible, transparent and explainable data and AI workflow with watsonx.governance You can learn more about what watsonx has to offer and how watsonx.ai

Automation 258

Automation Neural Network Natural Language Processing AI 258

IBM Journey to AI blog

JANUARY 10, 2024

Algorithms: Algorithms are the sets of rules AI systems use to process data and make decisions. The category of AI algorithms includes ML algorithms, which learn and make predictions and decisions without explicit programming. This is where AI programming offers a clear edge over rules-based programming methods.

Artificial Intelligence 229

Artificial Intelligence Artificial Intelligence Neural Network Algorithm 229

Marktechpost

DECEMBER 30, 2023

Users can try CodeGeeX online, providing natural language queries and selecting the target programming language for code generation. CodeGeeX leverages state-of-the-art natural language processing and deep learning techniques, enhancing accuracy and robustness.

AI Modeling 127

AI Modeling Natural Language Processing Python Machine Learning 127

Pickl AI

SEPTEMBER 23, 2024

Summary: This guide covers the most important Deep Learning interview questions, including foundational concepts, advanced techniques, and scenario-based inquiries. Gain insights into neural networks, optimisation methods, and troubleshooting tips to excel in Deep Learning interviews and showcase your expertise.

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Convolutional Neural Networks 52

Marktechpost

JUNE 9, 2024

It explains the differences between hand-coded algorithms and trained models, the relationship between machine learning and AI, and the impact of data types on training. It also explores neural networks, their components, and the complexity of deep learning.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Large Language Models 98

Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. Natural Language Processing (NLP) is a subfield of artificial intelligence.

Large Language Models 98

Large Language Models LLM Natural Language Processing Deep Learning 98

Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

Deep Learning 52

Deep Learning Neural Network Machine Learning Natural Language Processing 52

Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. It is a tremendous tool with the ability to completely alter numerous sectors.

Software Development 52

Software Development Deep Learning Neural Network Convolutional Neural Networks 52

Heartbeat

OCTOBER 11, 2023

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. Overfitting: When a machine learning model excels on the training data but fails to generalize to new data, overfitting has taken place.

Deep Learning 52

Deep Learning Machine Learning Neural Network Natural Language Processing 52

Marktechpost

MAY 29, 2024

Getting Started with Deep Learning This course teaches the fundamentals of deep learning through hands-on exercises in computer vision and natural language processing. Generative AI Explained This course provides an overview of Generative AI, its concepts, applications, challenges, and opportunities.

Neural Network 93

Neural Network Natural Language Processing Large Language Models Deep Learning 93

Heartbeat

MAY 2, 2023

Artificial intelligence has undergone a revolution thanks to deep learning. Deep learning allows machines to learn from vast amounts of data and carry out complex tasks that were previously only considered possible by humans (like translation between languages, recognizing objects etc.).

Deep Learning 52

Deep Learning Convolutional Neural Networks Algorithm Neural Network 52

Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). The introduction of the Transformer model was a significant leap forward for the concept of attention in deep learning. Vaswani et al.

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52

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 the vanishing and exploding gradient problems. said Ivern Ball.

Deep Learning 52

Deep Learning Neural Network Explainability Convolutional Neural Networks 52

Unite.AI

JUNE 13, 2024

These structured processes are necessary for developing robust and effective AI systems. Across fields such as Natural Language Processing (NLP) , computer vision , and recommendation systems , AI workflows power important applications like chatbots, sentiment analysis , image recognition, and personalized content delivery.

Natural Language Processing 147

Natural Language Processing Robotics AI AI 147