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. It covers AI fundamentals, including supervised learning and deep learning basics, without complex math.

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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

ODSC - Open Data Science

APRIL 28, 2023

If a Natural Language Processing (NLP) system does not have that context, we’d expect it not to get the joke. In this post, I’ll be demonstrating two deep learning approaches to sentiment analysis. Deep learning refers to the use of neural network architectures, characterized by their multi-layer design (i.e.

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Marktechpost

JULY 31, 2024

TensorFlow is a powerful open-source framework for building and deploying machine learning models. Learning TensorFlow enables you to create sophisticated neural networks for tasks like image recognition, natural language processing, and predictive analytics.

Neural Network 108

Neural Network Auto-classification Natural Language Processing Deep Learning 108

Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Whether you’re a beginner or an experienced practitioner, this guide will provide insights into the mechanics of artificial neural networks and their applications.

Convolutional Neural Networks 52

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Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

Neural Network 158

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Pickl AI

JANUARY 29, 2025

Summary: This article presents 10 engaging Deep Learning projects for beginners, covering areas like image classification, emotion recognition, and audio processing. Each project is designed to provide practical experience and enhance understanding of key concepts in Deep Learning. What is Deep Learning?

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Computer Vision 52

Unite.AI

OCTOBER 22, 2024

This term refers to how much time, memory, or processing power an algorithm requires as the size of the input grows. In AI, particularly in deep learning , this often means dealing with a rapidly increasing number of computations as models grow in size and handle larger datasets.

Neural Network 146

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Pickl AI

JANUARY 26, 2025

Summary: Deep Learning models revolutionise data processing, solving complex image recognition, NLP, and analytics tasks. Introduction Deep Learning models transform how we approach complex problems, offering powerful tools to analyse and interpret vast amounts of data. With a projected market growth from USD 6.4

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

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

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ODSC - Open Data Science

JULY 18, 2023

Here at ODSC, we couldn’t be more excited to announce Microsoft Azure’s tutorial series on Deep Learning and NLP, now available for free on Ai+. This team has a passion for fostering proficiency in AI, and can’t wait to help you deepen your knowledge in machine learning and deep learning. Sign me up!

Deep Learning 52

Deep Learning Convolutional Neural Networks NLP Neural Network 52

Viso.ai

OCTOBER 9, 2024

With the rapid development of Convolutional Neural Networks (CNNs) , deep learning became the new method of choice for emotion analysis tasks. Generally, the classifiers used for AI emotion recognition are based on Support Vector Machines (SVM) or Convolutional Neural Networks (CNN).

Convolutional Neural Networks 98

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Unite.AI

MARCH 26, 2024

The development of Large Language Models (LLMs) built from decoder-only transformer models has played a crucial role in transforming the Natural Language Processing (NLP) domain, as well as advancing diverse deep learning applications including reinforcement learning , time-series analysis, image processing, and much more.

Natural Language Processing 146

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Pickl AI

SEPTEMBER 16, 2024

Summary : Deep Belief Networks (DBNs) are Deep Learning models that use Restricted Boltzmann Machines and feedforward networks to learn hierarchical features and model complex data distributions. What is a Deep Belief Network (DBN)?

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Natural Language Processing 52

Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. This process is known as training, and it relies on large amounts of labeled data.

Deep Learning 52

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John Snow Labs

MAY 23, 2023

Visual question answering (VQA), an area that intersects the fields of Deep Learning, Natural Language Processing (NLP) and Computer Vision (CV) is garnering a lot of interest in research circles. For visual question answering in Deep Learning using NLP, public datasets play a crucial role.

Natural Language Processing 40

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Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. These algorithms can learn and extract intricate features from input images by using convolutional layers.

Natural Language Processing 52

Natural Language Processing Computer Vision NLP Algorithm 52

John Snow Labs

JUNE 2, 2023

Sentiment analysis, also known as opinion mining, is the process of computationally identifying and categorizing the subjective information contained in natural language text. Deep learning models can automatically learn features and representations from raw text data, making them well-suited for sentiment analysis tasks.

Deep Learning 76

Deep Learning NLP Convolutional Neural Networks Neural Network 76

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

Marktechpost

DECEMBER 10, 2024

1943: McCulloch and Pitts created a mathematical model for neural networks, marking the theoretical inception of ANNs. 1958: Frank Rosenblatt introduced the Perceptron , the first machine capable of learning, laying the groundwork for neural network applications. How Do Artificial Neural Networks Work?

Neural Network 109

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

Computer Vision 52

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Viso.ai

DECEMBER 10, 2023

Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. I n past years, machine learning, in particular deep learning technology , has achieved big successes in many computer vision and image understanding tasks.

Convolutional Neural Networks 98

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Pickl AI

FEBRUARY 7, 2025

Summary: Machine Learning and Deep Learning are AI subsets with distinct applications. ML works with structured data, while DL processes complex, unstructured data. Introduction In todays world of AI, both Machine Learning (ML) and Deep Learning (DL) are transforming industries, yet many confuse the two.

Deep Learning 52

Deep Learning Machine Learning Neural Network Convolutional Neural Networks 52

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

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.

Software Development 52

Software Development Deep Learning Neural Network Convolutional Neural Networks 52

Marktechpost

SEPTEMBER 17, 2024

In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and time. Researchers have been exploring advanced optimization techniques to make this process more efficient.

Neural Network 113

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 113

Pickl AI

SEPTEMBER 25, 2024

Summary: This blog delves into 20 Deep Learning applications that are revolutionising various industries in 2024. From healthcare to finance, retail to autonomous vehicles, Deep Learning is driving efficiency, personalization, and innovation across sectors.

Deep Learning 52

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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.

NLP 98

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IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification.

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

Pickl AI

FEBRUARY 1, 2023

Transfer Learning in Deep Learning: A Brief Overview Collecting large volumes of data, filtering it and then interpreting is a challenging task. Yes, Transfer Learning is the answer to it. What is Transfer Learning? Eventually, making it a powerful and efficient tool in Machine Learning.

Deep Learning 52

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Heartbeat

FEBRUARY 22, 2023

Deep learning for feature extraction, ensemble models, and more Photo by DeepMind on Unsplash The advent of deep learning has been a game-changer in machine learning, paving the way for the creation of complex models capable of feats previously thought impossible.

Deep Learning 52

Deep Learning Machine Learning Convolutional Neural Networks Computer Vision 52

Pickl AI

NOVEMBER 13, 2024

Summary: Batch Normalization in Deep Learning improves training stability, reduces sensitivity to hyperparameters, and speeds up convergence by normalising layer inputs. It’s a crucial technique in modern neural networks, enhancing performance and generalisation. The global Deep Learning market, valued at $17.60

Deep Learning 52

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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. The typical architecture of a neural machine translation model (NMT).

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52

Unite.AI

JULY 31, 2023

This approach is known as self-supervised learning , and it’s one of the most efficient methods to build ML and AI models that have the “ common sense ” or background knowledge to solve problems that are beyond the capabilities of AI models today. It’s precisely the question that the SEER model aims to answer.

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Pickl AI

NOVEMBER 28, 2024

Summary: Gradient descent is a fundamental optimisation technique in Deep Learning crucial for minimising loss functions and enhancing model accuracy. Understanding its types—Batch, Stochastic, and Mini-batch Gradient Descent—enables effective training of complex neural networks. What is Gradient Descent?

Deep Learning 52

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Heartbeat

JUNE 23, 2023

However, with the advent of deep learning, researchers have explored various neural network architectures to model and forecast time series data. In this post, we will look at deep learning approaches for time series analysis and how they might be used in real-world applications. Let’s dive in!

Deep Learning 52

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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? Describe the architecture of a Convolutional Neural Network (CNN) in detail.

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