insideBIGDATA

OCTOBER 22, 2024

We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. The team here at insideAI News is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.

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insideBIGDATA

MARCH 18, 2024

Today at NVIDIA GTC, Hewlett Packard Enterprise (NYSE: HPE) announced updates to one of the industry’s most comprehensive AI-native portfolios to advance the operationalization of generative AI (GenAI), deep learning, and machine learning (ML) applications.

Deep Learning 464

Deep Learning Deep Learning Machine Learning Machine Learning 464

insideBIGDATA

FEBRUARY 15, 2023

This paper is a major turning point in deep learning research. In this video presentation, Mohammad Namvarpour presents a comprehensive study on Ashish Vaswani and his coauthors' renowned paper, “Attention Is All You Need.”

Natural Language Processing 497

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insideBIGDATA

JANUARY 18, 2024

We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.

Big Data 513

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Analytics Vidhya

FEBRUARY 27, 2025

As part of #OpenSourceWeek Day 4, DeepSeek introduces 2 new tools to make deep learning faster and more efficient: DualPipe and EPLB. These tools help improve how computers handle calculations and communication during training, making the process smoother and quicker.

Deep Learning 187

Deep Learning Deep Learning Analytics Analytics 187

insideBIGDATA

MARCH 7, 2023

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday.

Deep Learning 515

Deep Learning Deep Learning Big Data Big Data 515

Analytics Vidhya

OCTOBER 14, 2024

They use deep learning techniques, particularly transformers, to perform various language tasks such as translation, text generation, and summarization. […] The post 12 Free And Paid LLMs for Your Daily Tasks appeared first on Analytics Vidhya.

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insideBIGDATA

JANUARY 17, 2023

We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.

Big Data 482

Big Data Big Data Deep Learning Deep Learning 482

insideBIGDATA

OCTOBER 11, 2023

We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.

Big Data 474

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Machine Learning Research at Apple

APRIL 20, 2025

This week, the Thirteenth International Conference on Learning Representations (ICLR) will be held in Singapore. ICLR brings together leading experts on deep learning and the application of representation

Machine Learning 213

Machine Learning Machine Learning Deep Learning Deep Learning 213

Flipboard

MARCH 24, 2025

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet , the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 by proving that "deep learning" could achieve things conventional AI techniques could not.

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insideBIGDATA

APRIL 17, 2023

We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.

Big Data 459

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KDnuggets

APRIL 19, 2024

The collection includes free courses on Python, SQL, Data Analytics, Business Intelligence, Data Engineering, Machine Learning, Deep Learning, Generative AI, and MLOps.

Data Science 380

Data Science Deep Learning Deep Learning Business Intelligence 380

insideBIGDATA

OCTOBER 23, 2023

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday.

Deep Learning 418

Deep Learning Deep Learning Big Data Big Data 418

KDnuggets

OCTOBER 8, 2024

With Hugging Face become prominent than ever, learning how to use the Transformers library with popular deep-learning frameworks would improve your career.

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Deep Learning Deep Learning 335

insideBIGDATA

DECEMBER 10, 2023

Welcome insideBIGDATA AI News Briefs Bulletin Board, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deep learning, large language models, generative AI, and transformers.

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Hacker News

APRIL 28, 2025

Relational Graph Transformers represent the next evolution in Relational Deep Learning, allowing AI systems to seamlessly navigate and learn from data spread across multiple tables.

Data Pipeline 109

Data Pipeline Deep Learning Deep Learning Database 109

Machine Learning Mastery

MARCH 28, 2025

Transformer is a deep learning architecture that is very popular in natural language processing (NLP) tasks. Specifically, you will learn: What problems do the transformer models address What is… It is a type of neural network that is designed to process sequential data, such as text.

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Data Science Dojo

FEBRUARY 13, 2025

The notable features of the IEEE conference are: Cutting-Edge AI Research & Innovations Gain exclusive insights into the latest breakthroughs in artificial intelligence, including advancements in deep learning, NLP, and AI-driven automation.

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Hacker News

APRIL 13, 2025

The canonical deep learning approach for learning requires computing a gradient term at each layer by back-propagating the error signal from the output towards each learnable parameter.

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Deep Learning Deep Learning Algorithm 135

Towards AI

APRIL 18, 2025

These include tools for development environments, deep learning frameworks, machine learning lifecycle management, workflow orchestration, and large language models. Machine Learning & Data Science PythonJupyter Notebook data science stack II. Generative AI & Deep Learning 3. TensorFlow 6.

ML 94

ML ML Deep Learning Deep Learning 94

Data Science Dojo

NOVEMBER 10, 2023

Jax: Jax is a high-performance numerical computation library for Python with a focus on machine learning and deep learning research. It is developed by Google AI and has been used to achieve state-of-the-art results in a variety of machine learning tasks, including generative AI.

Python 524

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Flipboard

APRIL 24, 2025

MIT LIDS researchers have developed a new way of approaching complex problems such as coordinating complicated interactive systems, using simple diagrams as a tool to reveal better approaches to software optimization in deep learning models.

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Deep Learning Deep Learning Algorithm Computer Science 175

Dataconomy

APRIL 28, 2025

The Segment Anything Model (SAM) represents a significant advancement in the field of image segmentation, leveraging deep learning to redefine how multiple objects can be identified and delineated in images. Key features of SAM SAM is built on powerful deep learning frameworks, enabling it to achieve exceptional performance.

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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). Programming: Learn Python, as its the most widely used language in AI/ML. Why Become a Generative AI Engineer in 2025?

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Towards AI

DECEMBER 21, 2024

Tasks like splitting timestamps for session analysis or encoding categorical variables had to be scripted manually.Model Building: I would use Scikit-learn or XGBoost for collaborative filtering and content-based methods. For deep learning, I used TensorFlow 1.x,

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PyImageSearch

DECEMBER 9, 2024

The next step for researchers was to use deep learning approaches such as NeRFs and 3D Gaussian Splatting, which have shown promising results in novel view synthesis, computer graphics, high-resolution image generation, and real-time rendering. In short, it’s a basic reconstruction. Or requires a degree in computer science?

Deep Learning 110

Deep Learning Deep Learning Algorithm Computer Science 110

Flipboard

APRIL 6, 2025

We used a state-of-the-art generative deep learning model for generating such imaging templates. In the second step, we apply deep learning-based diffeomorphic registration to align the given image of a subject with a reference imaging template.

Deep Learning 73

Deep Learning Deep Learning Machine Learning Machine Learning 73

Dataconomy

MARCH 21, 2025

Approaches to NLP NLP can be broadly categorized into rule-based systems and machine learning systems. Rule-based systems utilize predefined linguistic rules to analyze text, while machine learning systems rely on data-driven approaches to train models. NLP Architect by Intel: A deep learning toolkit for NLP and text processing.

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Dataconomy

FEBRUARY 26, 2025

However, while deep learning models have significantly improved HAR accuracy, they often operate as “black boxes,” offering little transparency into their decision-making process. This innovative model not only improves HAR performance but also generates human-readable explanations for its predictions.

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Dataconomy

APRIL 17, 2025

Frequently leveraging deep learning techniques, this method allows for creative and practical applications across diverse fields, from artistic endeavors to medical imaging. What is image-to-image translation?

Deep Learning 91

Deep Learning Deep Learning Supervised Learning Algorithm 91

Dataconomy

APRIL 21, 2025

Neural network tuning is a fascinating area within deep learning that can significantly impact model performance. This process not only improves results but also provides valuable insights into the models workings, making it a crucial aspect of machine learning projects. What is neural network tuning?

Deep Learning 91

Deep Learning Deep Learning Machine Learning Machine Learning 91

Flipboard

MARCH 17, 2025

Course information: 86+ total classes 115+ hours hours of on-demand code walkthrough videos Last updated: March 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?

Python 153

Python Deep Learning Deep Learning Machine Learning 153

PyImageSearch

JANUARY 13, 2025

Figure 13: Multi-Object Tracking for Pose Estimation (source: output video generated by running the above code) How to Train with YOLO11 Training a deep learning model is a crucial step in building a solution for tasks like object detection. Or has to involve complex mathematics and equations? Or requires a degree in computer science?

Python 105

Python Deep Learning Deep Learning Computer Science 105

Data Science Dojo

MAY 27, 2024

A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. This breakthrough has profound implications for drug development, as understanding protein structures can aid in designing more effective therapeutics.

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Dataconomy

FEBRUARY 21, 2025

Using deep learning and transformer-based models, SparkAI processes extensive audio datasets to analyze tonal characteristics and generate realistic guitar sounds. The system applies self-supervised learning techniques, allowing it to adapt to different playing styles without requiring manually labeled training data.

Supervised Learning 113

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Dataconomy

MARCH 17, 2025

Dropout in deep learning In deep learning, dropout is a regularization technique where random neurons are excluded during training. This process encourages the model to learn robust features that are not reliant on any single neuron, thereby improving generalization.

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Machine Learning Machine Learning Cross Validation Deep Learning 103