Artificial Corner

JANUARY 23, 2025

2 Python for Data Analysis Course This one is more like a playlist than a course; however, you will find more useful lectures in this playlist than in some paid courses. The first 8 videos in the playlist make a 10-hour data analysis course. 4 Machine Learning & Artificial Intelligence with Tensorflow 2.0

Data Science 95

Data Science Python Convolutional Neural Networks Natural Language Processing 95

Marktechpost

NOVEMBER 10, 2023

Traditionally, Convolutional Neural Networks (CNNs) have been the go-to models for processing image data, leveraging their ability to extract meaningful features and classify visual information.

Convolutional Neural Networks 109

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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

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. A VQA system takes free-form, text-based questions about an input image and presents answers in a natural language format.

Natural Language Processing 40

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Chatbots Life

APRIL 16, 2024

This is useful in natural language processing tasks. Anomaly Detection Generative models can detect anomalies in data by identifying samples that deviate significantly from the learned distribution. Convolutional Neural Networks (CNN): CNNs are specialized deep learning models commonly used for image classification tasks.

Neural Network 59

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 59

Mlearning.ai

MAY 30, 2023

RNNs have demonstrated their value by simulating the temporal relationships evident in sequential data, whether it be for stock price prediction, text generation, or speech recognition. As we know that Convolutional Neural Network (CNN) is used for structured arrays of data such as image data.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 52

Marktechpost

NOVEMBER 27, 2024

5) K-Means Clustering K-means clustering is a popular unsupervised machine learning algorithm used for grouping similar data points. It’s a fundamental technique for exploratory data analysis and pattern recognition. Randomly select k data points as initial cluster centroids. Image recognition. (

Machine Learning 113

Machine Learning Algorithm Neural Network Convolutional Neural Networks 113

Pickl AI

SEPTEMBER 3, 2024

Here are some core responsibilities and applications of ANNs: Pattern Recognition ANNs excel in recognising patterns within data , making them ideal for tasks such as image recognition, speech recognition, and natural language processing. Frequently Asked Questions What are the main types of Artificial Neural Network?

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 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. At the core of Deep Learning is the artificial neural network (ANN), which is inspired by the structure and function of the human brain.

Deep Learning 52

Deep Learning Machine Learning Algorithm Neural Network 52

Viso.ai

OCTOBER 10, 2024

Pattern Recognition in Data Analysis What is Pattern Recognition? Pattern recognition is useful for a multitude of applications, specifically in statistical data analysis and image analysis. This guide provides an overview of the most important techniques used to recognize patterns and real-world applications.

Neural Network 98

Neural Network Computer Vision Deep Learning Machine Learning 98

Viso.ai

DECEMBER 20, 2023

In general, supervised learning is more widely used than unsupervised learning because it requires less data and is easier to implement because the output data is predefined. This can be used for fraud detection, identification of errors in data, and finding unusual patterns.

Computer Vision 98

Computer Vision Machine Learning Neural Network Algorithm 98

Viso.ai

DECEMBER 1, 2023

VGG Deep Convolutional Neural Network Architecture YOLO, or “You Only Look Once,” is a deep learning model for real-time object detection. developed by Mistral AI, was their first Large Language Model (LLMs). To learn more about this AI model, read our guide about how Deep Neural Network models work.

AI Modeling 98

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Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. At the same time, Keras is a high-level neural network API that runs on top of TensorFlow and simplifies the process of building and training deep learning models.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Neural Network 52

Pickl AI

FEBRUARY 7, 2025

These networks can automatically discover patterns and features without explicit programming, making deep learning ideal for tasks requiring high levels of complexity, such as speech recognition and natural language processing. Its ability to learn from large volumes of data makes it ideal for complex applications.

Deep Learning 52

Deep Learning Machine Learning Neural Network Convolutional Neural Networks 52

Pickl AI

OCTOBER 2, 2024

Genomic Analysis is crucial for various applications, including personalised medicine, cancer research, genetic disorder diagnosis, and evolutionary biology. AI Techniques Used in Genomic Analysis AI encompasses a range of techniques that can be applied to genomic Data Analysis.

Neural Network 52

Neural Network Deep Learning Machine Learning Artificial Intelligence 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

Deep Learning Algorithm Convolutional Neural Networks Neural Network 52

Viso.ai

APRIL 17, 2024

Deep Learning extensively utilizes Convolutional Neural Networks (CNNs) in which convolution operations play a central role in automatic feature extraction. The primary goal of using convolution in image processing is to extract important features from the image and discard the rest.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning Natural Language Processing 52

Viso.ai

MARCH 26, 2024

Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. 2: Automated Document Analysis and Processing No.3: 4: Algorithmic Trading and Market Analysis No.5: 1: Fraud Detection and Prevention No.2:

Computer Vision 52

Computer Vision Neural Network Machine Learning Convolutional Neural Networks 52

Viso.ai

OCTOBER 17, 2024

Feedforward neural networks on the other hand are more traditional one-way networks, where data flows in one direction (forward) which is the opposite of RNNs that have loops. One of those advancements was Convolutional Neural Networks (CNNs) which were trained by backpropagation.

Neural Network 52

Neural Network Deep Learning Machine Learning Computer Vision 52

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 Automation 52

Pickl AI

NOVEMBER 28, 2024

These networks can learn from large volumes of data and are particularly effective in handling tasks such as image recognition and natural language processing. Key Deep Learning models include: Convolutional Neural Networks (CNNs) CNNs are designed to process structured grid data, such as images.

Machine Learning 52

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Viso.ai

JULY 9, 2024

On the other hand, the generative AI task is to create new data points that look like the existing ones. Discriminative models include a wide range of models, like Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Support Vector Machines (SVMs), or even simpler models like random forests.

Generative AI 52

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PyImageSearch

FEBRUARY 19, 2024

text generation and data analysis). 3f' % (epoch + 1, i + 1, running_loss / 2000)) running_loss = 0.0 # Test the Model correct = 0 total = 0 with torch.no_grad(): for data in test_loader: images, labels = data outputs = model(images) _, predicted = torch.max(outputs.data, 1) total += labels.size(0) correct += (predicted == labels).sum().item()

Computer Vision 59

Computer Vision ChatGPT Deep Learning Python 59

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. Thus, positioning him as one of the top AI influencers in the world.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

John Snow Labs

MAY 8, 2024

The potential of LLMs, in the field of pathology goes beyond automating data analysis. As we navigate the complexities associated with integrating AI into healthcare practices our primary focus remains on using this technology to maximize its advantages while protecting rights and ensuring data privacy.

Large Language Models 40

Large Language Models Automation NLP Machine Learning 40