Unite.AI

NOVEMBER 6, 2023

For instance, NN used for computer vision tasks (object detection and image segmentation) are called convolutional neural networks (CNNs) , such as AlexNet , ResNet , and YOLO. Today, generative AI technology is taking neural network techniques one step further, allowing it to excel in various AI domains.

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Towards AI

MARCH 3, 2025

Can machines understand human language? These questions are addressed by the field of Natural Language processing, which allows machines to mimic human comprehension and usage of natural language. Last Updated on March 3, 2025 by Editorial Team Author(s): SHARON ZACHARIA Originally published on Towards AI.

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ODSC - Open Data Science

FEBRUARY 10, 2025

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. Speech Recognition Audio analysis is central to speech and voice recognition.

Machine Learning 52

Machine Learning Convolutional Neural Networks Neural Network Natural Language Processing 52

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

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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. We’ll be specifying a “textcat” component, the “model” that will process text into spaCy Doc objects. Since 2014, he has been working in data science for government, academia, and the private sector.

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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.

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ODSC - Open Data Science

JULY 18, 2023

Series Introduction The first session will provide you with an introduction to this series, as well as the fundamentals of machine learning and deep learning with a focus on fully connected and convolution neural networks. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Deep Learning 52

Deep Learning Convolutional Neural Networks NLP Neural Network 52

Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

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Heartbeat

MAY 2, 2023

Neural Networks Neural networks are a popular deep learning algorithm that are inspired by the structure and function of the human brain. They have several use cases, from image recognition to natural language processing and self-driving vehicles.

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Marktechpost

DECEMBER 12, 2024

The deep aspect of DNNs comes from multiple hidden layers, which allow the network to learn and model complex patterns and relationships in data. DNNs are the backbone of many advanced artificial intelligence applications, including image recognition, natural language processing, and autonomous systems.

Neural Network 57

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Pickl AI

AUGUST 14, 2024

They consist of interconnected nodes that learn complex patterns in data. Different types of neural networks, such as feedforward, convolutional, and recurrent networks, are designed for specific tasks like image recognition, Natural Language Processing, and sequence modelling.

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Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Heartbeat

AUGUST 15, 2023

Advanced techniques have been devised to address these challenges, such as deep learning, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Specifically, we will discuss CNNs, RNNs, data augmentation, transfer learning, and ensemble models.

Python 52

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How to Learn Machine Learning

DECEMBER 15, 2024

Whether you’re a complete beginner or an experienced professional looking to upgrade your skills, these courses provide the knowledge and practical experience needed to excel in the world of data science and artificial intelligence. Ready to start your machine learning journey?

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Software Engineer 52

Heartbeat

MARCH 8, 2023

Happy Reading, Emilie, Abby & the Heartbeat Team Natural Language Processing With SpaCy (A Python Library) — by Khushboo Kumari This post goes over how the most cutting-edge NLP software, SpaCy , operates. But instead of just tuning specific hyperparameters, we can also decide how our network is shaped.

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Heartbeat

JUNE 6, 2023

GCNs have been successfully applied to many domains, including computer vision and social network analysis. In recent years, researchers have also explored using GCNs for natural language processing (NLP) tasks, such as text classification , sentiment analysis , and entity recognition.

NLP 59

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Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. Here, she studied statistics, neuroscience, and psychology.

Convolutional Neural Networks 52

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Pickl AI

FEBRUARY 1, 2023

This technology allows models to be fine-tuned using a limited amount of data. It is especially useful in applications where labelled datasets are scarce or expensive to acquire, such as medical imaging, autonomous driving, and Natural Language Processing (NLP). Thus it is computationally lesser expensive.

Deep Learning 52

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Heartbeat

MAY 30, 2023

Natural Language Processing : DRL has been used for enhancing chatbots, machine translations, speech recognition, etc DRL for robotics; image from TechXplore We could go on and on about Deep Reinforcement Learning’s applications, from training self-driving cars to creating game-playing agents that outperform human players.

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How to Learn Machine Learning

AUGUST 15, 2024

Projects to Tackle for Your Machine Learning Portfolio To build a comprehensive portfolio, consider including projects from various domains and complexity levels: Image Classification : Develop a model to classify images using convolutional neural networks (CNNs).

Machine Learning 64

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How to Learn Machine Learning

MAY 14, 2023

When selecting projects, consider tackling problems in different domains, such as natural language processing, computer vision, or recommendation systems. Some popular areas of specialization include natural language processing, computer vision, and reinforcement learning.

Machine Learning 52

Machine Learning Natural Language Processing Convolutional Neural Networks Deep Learning 52

Heartbeat

NOVEMBER 21, 2023

From object detection and recognition to natural language processing, deep reinforcement learning, and generative models, we will explore how deep learning algorithms have conquered one computer vision challenge after another. One of the most significant breakthroughs in this field is the convolutional neural network (CNN).

Computer Vision 52

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Pickl AI

JULY 16, 2023

Its primary focus lies in deep learning, allowing developers to construct neural networks and train models for tasks such as image recognition, natural language processing, and more. Neural Network Design There is a rich set of tools and functionalities for designing and implementing neural networks.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Python 52

Heartbeat

JANUARY 12, 2023

Other practical examples of deep learning include virtual assistants, chatbots, robotics, image restoration, NLP (Natural Language Processing), and so on. Convolution, pooling, and fully connected layers are just a few components that make up a convolutional neural network.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Heartbeat

JULY 6, 2023

The process of locating and identifying objects of interest in an image or video is part of the object detection method, a popular computer vision technique. Object detection is typically achieved through the use of deep learning models, particularly Convolutional Neural Networks (CNNs).

Computer Vision 59

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Pickl AI

JULY 22, 2024

Summary: Probabilistic model in Machine Learning handle uncertainty and complex data structures, improving decision-making and predictions. Introduction Machine Learning models are essential tools in Data Science , designed to predict outcomes and uncover patterns from data. Explore: What is Tokenization in NLP?

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Heartbeat

FEBRUARY 22, 2023

These models have been used to achieve state-of-the-art performance in many different fields, including image classification, natural language processing, and speech recognition. However, the best approach will always differ depending on the specifics of the problem at hand and the data at hand.

Deep Learning 52

Deep Learning Machine Learning Convolutional Neural Networks Computer Vision 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. Speech and Audio Processing : Speaker identification, speech recognition, creation of music, etc.

Software Development 52

Software Development Deep Learning Neural Network Convolutional Neural Networks 52

Heartbeat

AUGUST 22, 2023

Introduction Text classification is the process of automatically assigning a set of predefined categories or labels to a piece of text. It’s an essential task in natural language processing (NLP) and machine learning, with applications ranging from sentiment analysis to spam detection. You can get the dataset here.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Pickl AI

SEPTEMBER 23, 2024

Gain insights into neural networks, optimisation methods, and troubleshooting tips to excel in Deep Learning interviews and showcase your expertise. In image recognition, Convolutional Neural Networks (CNNs) can accurately identify objects and faces in images. Describe the Architecture of Transformer Models.

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Convolutional Neural Networks 52

Pickl AI

AUGUST 1, 2023

Machine Learning models play a crucial role in this process, serving as the backbone for various applications, from image recognition to natural language processing. In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types. What is Machine Learning?

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Pickl AI

JULY 14, 2023

Deep Learning, a subfield of ML, gained attention with the development of deep neural networks. Moreover, Deep Learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), achieved remarkable breakthroughs in image classification, natural language processing, and other domains.

Neural Network 52

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Viso.ai

SEPTEMBER 2, 2024

In this article, we introduce several positions in the world of computer vision (CV) aside from computer vision engineers, or AI/machine learning/data science specialists. Experience with classical computer vision tools, such as OpenCV , object detection, image segmentation, data annotation, etc.

Computer Vision 52

Computer Vision Software Engineer Convolutional Neural Networks Neural Network 52

Pickl AI

OCTOBER 2, 2024

Read More: Supervised Learning vs Unsupervised Learning Deep Learning Deep Learning is a subset of Machine Learning that uses neural networks with multiple layers to analyse complex data patterns. It has shown great promise in Genomic Analysis due to its ability to handle high-dimensional data.

Neural Network 52

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Pickl AI

DECEMBER 10, 2024

Image Data Image features involve identifying visual patterns like edges, shapes, or textures. Methods like Histogram of Oriented Gradients (HOG) or Deep Learning models, particularly Convolutional Neural Networks (CNNs), effectively extract meaningful representations from images.

Machine Learning 52

Machine Learning Convolutional Neural Networks Categorization Deep Learning 52

Pickl AI

SEPTEMBER 25, 2024

Natural Language Processing (NLP) NLP applications powered by Deep Learning have transformed how machines understand human language. Chatbots and Virtual Assistants These AI-driven tools utilise Deep Learning to provide customer support through natural language conversations.

Deep Learning 52

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Heartbeat

MARCH 5, 2024

Researchers and practitioners in computer vision continue to work on addressing these challenges through advancements in deep learning techniques, data augmentation, transfer learning, and domain adaptation. What Is Image Augmentation? We're committed to supporting and inspiring developers and engineers from all walks of life.

Computer Vision 52

Computer Vision Deep Learning Convolutional Neural Networks Machine Learning 52

Heartbeat

FEBRUARY 8, 2024

Photo in pexel.com With technological advancements, many multimedia data requests efficient ways to search for and obtain information across several methodologies. Cross-modal retrieval is a branch of computer vision and natural language processing that links visual and verbal descriptions.

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